Find the best Data Engineers in Berlin in minutes from 15,000 CVs with the power of AI
Need help with ETL and ELT pipelines, warehouse modeling, or streaming data on Snowflake, BigQuery, Databricks, and Kafka? Get fast, precise matching with vetted, available freelancers.
About the role
Data pipelines
A Data Engineer builds the flow that turns raw data into usable data. That usually means ingesting from APIs, databases, SaaS tools, logs, and event streams, then transforming it into reliable tables for analytics, reporting, and machine learning. Typical deliverables include:
- Batch and streaming pipelines
- ETL and ELT workflows
- Data warehouse and lakehouse models
- Data quality checks and monitoring
- Documentation for handover and support
Skills and tools Strong data engineers combine software engineering discipline with data platform know-how. They work comfortably with SQL, Python, orchestration tools, and cloud services, and they understand how to keep pipelines maintainable under changing source systems.
- SQL, Python, and data modeling
- Airflow, dbt, Spark, and Kafka
- Snowflake, BigQuery, Databricks, and Redshift
- Version control, testing, and observability
- Access control and secure data handling
When companies hire Companies bring in freelance data engineers when data work is urgent, scoped, or tied to a platform change. Common cases include a new warehouse rollout, broken pipelines after a system migration, messy source data that blocks dashboards, or a need to scale a team without adding permanent headcount. In Berlin, this often fits product companies, SaaS teams, e-commerce businesses, and firms with mixed local and remote teams. A freelancer can also help when the work needs to start quickly and the internal team is busy with delivery.
What good looks like A strong data engineer does more than move data. They ask where the data comes from, who uses it, what can fail, and how the team will maintain it after launch.
- Clear data models that match business use
- Stable pipelines with meaningful alerts
- Clean handover for analysts and engineers
- Practical choices, not overbuilt solutions
- Good communication with product, analytics, and backend teams
Common specialisms The title covers several nearby roles that buyers often search under. You may also see ETL developer, data pipeline engineer, analytics engineer, or cloud data engineer when the work is focused on transformation, warehouse layers, or platform operations. The right freelancer depends on whether you need ingestion, modeling, real-time processing, or support for a full data stack. For example, a team may need help connecting operational systems to a central warehouse, or building a reliable layer for BI tools such as Looker, Power BI, or Tableau.
Working setup Freelance data engineers usually work remotely with access to source systems, cloud accounts, and a clear ticket backlog. On-site time in Berlin can help during discovery, architecture discussions, or a sensitive migration, but it is not always necessary for delivery. What matters most is tight collaboration with analytics, backend, and platform teams, plus a clear definition of ownership. Good freelancers can join an existing stack, improve it without disruption, and leave the team with code that is easy to maintain.
Meet FRATCH Data Engineers
Alexander Zhirov
Senior Data Architect & Data Engineer
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Anshita Srivastava
Data & Analytics Professional
Last position:
Business Intelligence Developer and Data Analyst at Deloitte Consulting
Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to deliver a new generation of self-service tools and analytics services.
- Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
- Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
- Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
- Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
- BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.
Anshita Srivastava
Data & Analytics Professional
Last position:
Business Intelligence Developer and Data Analyst at Deloitte Consulting
Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to
Specialize in turning complex data from diverse environments into actionable business value through compelling visual storytelling. I am an expert in generating actionable insights and presenting recommendations to business stakeholders. My technical proficiency in SQL, Python, and leading data visualization tools like Tableau and Power BI allows me to deliver a new generation of self-service tools and analytics services.
- Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
- Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
- Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
- Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
- BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.
deliver a new generation of self-service tools and analytics services.
- Data Visualization & Storytelling: Created impactful data visualizations and dashboards in Tableau and Power BI, effectively communicating findings and presenting actionable recommendations to C-suite stakeholders and business leaders.
- Stakeholder Management: Built effective working relationships with key business stakeholders, data engineers, and other partners to achieve common data-driven goals and targets.
- Insights & Recommendations: Generated actionable insights from complex data analysis for funnel conversion, marketing performance, and ROI, directly influencing business performance and strategy.
- Data Collaboration & Empowerment: Worked closely with cross-functional teams to support the ongoing data needs of internal partners, helping to optimize internal data processes and workflows.
- BI & Data Expertise: Applied extensive experience in data modeling, data collection, data mining, and analysis to deliver end-to-end analytical solutions from stakeholder discovery to production.
Tobias Lewen
Data Engineer
Last position:
Data Engineer at unitb consulting GmbH
Tasks: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.
Activities:
- Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
- Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
- Developed automated data pipelines with Python, dbt, and GCP services for different data sources
- Built monitoring and alerting systems for real-time platform monitoring
- Implemented data versioning and quality checks at every layer
- Designed automated test and deployment pipelines in GitLab and Bitbucket
Achievements:
- 2× production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
- Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, configuration errors to 0
- Delivered a complete end-to-end data platform at ~€10/month infrastructure cost
- Migrated 7 database tables with 0 downstream issues
- Removed 100% exposed credentials, eliminated external vendor dependency
- Delivered integration of 3 teams in 1 sprint
Tobias Lewen
Data Engineer
Last position:
Data Engineer at unitb consulting GmbH
Tasks: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.
Activities:
- Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
Tasks: Design and operation of end-to-end cloud data platforms for enterprise clients in publishing and finance, including infrastructure automation, pipeline development, monitoring, and data quality.
Activities:
- Built multi-layer data architectures on Databricks (Apache Spark, Delta Lake), BigQuery, and GCP
- Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
- Developed automated data pipelines with Python, dbt, and GCP services for different data sources
- Built monitoring and alerting systems for real-time platform monitoring
- Implemented data versioning and quality checks at every layer
- Designed automated test and deployment pipelines in GitLab and Bitbucket
Achievements:
- 2× production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
- Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, configuration errors to 0
- Delivered a complete end-to-end data platform at ~€10/month infrastructure cost
- Migrated 7 database tables with 0 downstream issues
- Removed 100% exposed credentials, eliminated external vendor dependency
- Delivered integration of 3 teams in 1 sprint
- Fully automated cloud infrastructure with Terraform across 3 environments (DEV/STG/PRD)
- Developed automated data pipelines with Python, dbt, and GCP services for different data sources
- Built monitoring and alerting systems for real-time platform monitoring
- Implemented data versioning and quality checks at every layer
- Designed automated test and deployment pipelines in GitLab and Bitbucket
Achievements:
- 2× production data processing capacity, reduced spike response time from minutes to ≤15 s, server errors ≈ 0
- Replaced 3,000 lines of manual configuration with a reusable automation module for 7 customer domains, configuration errors to 0
- Delivered a complete end-to-end data platform at ~€10/month infrastructure cost
- Migrated 7 database tables with 0 downstream issues
- Removed 100% exposed credentials, eliminated external vendor dependency
- Delivered integration of 3 teams in 1 sprint
Lasya Marella
Data Engineer
Last position:
Data Engineer at Carelon Global Solutions (Elevance Health)
- Designed and implemented scalable ETL/ELT pipelines using Python, SQL, dbt, AWS and Informatica to ingest data from sources such as APIs, relational databases, and flat files into Snowflake, reducing pipeline runtime by ~30%.
- Migrated high-volume datasets from on-premises Teradata to Snowflake using AWS services (S3, Glue, Step Functions, IAM), ensuring data consistency and integrity.
- Applied Kimball methodology to design star and snowflake schemas, improving query performance and reducing Snowflake compute costs.
- Implemented automated data quality checks using SQL-based dbt tests and the Great Expectations framework to detect anomalies and enforce data correctness before production loads.
- Orchestrated ETL workflows in Airflow using Python and managed code deployments via Git with CI/CD best practices to increase deployment reliability and maintain pipeline uptime.
- Built interactive Power BI dashboards and curated datasets to enable data-driven decision-making for stakeholders.
- Maintained technical documentation in Confluence for ETL workflows, and led knowledge-sharing sessions for new joiners.
Lasya Marella
Data Engineer
Last position:
Data Engineer at Carelon Global Solutions (Elevance Health)
- Designed and implemented scalable ETL/ELT pipelines using Python, SQL, dbt, AWS and Informatica to ingest data from sources such as APIs, relational databases, and flat files into Snowflake, reducing pipeline runtime by ~30%.
- Designed and implemented scalable ETL/ELT pipelines using Python, SQL, dbt, AWS and Informatica to ingest data from sources such as APIs, relational databases, and flat files into Snowflake, reducing pipeline runtime by ~30%.
- Migrated high-volume datasets from on-premises Teradata to Snowflake using AWS services (S3, Glue, Step Functions, IAM), ensuring data consistency and integrity.
- Applied Kimball methodology to design star and snowflake schemas, improving query performance and reducing Snowflake compute costs.
- Implemented automated data quality checks using SQL-based dbt tests and the Great Expectations framework to detect anomalies and enforce data correctness before production loads.
- Orchestrated ETL workflows in Airflow using Python and managed code deployments via Git with CI/CD best practices to increase deployment reliability and maintain pipeline uptime.
- Built interactive Power BI dashboards and curated datasets to enable data-driven decision-making for stakeholders.
- Maintained technical documentation in Confluence for ETL workflows, and led knowledge-sharing sessions for new joiners.
- Migrated high-volume datasets from on-premises Teradata to Snowflake using AWS services (S3, Glue, Step Functions, IAM), ensuring data consistency and integrity.
- Applied Kimball methodology to design star and snowflake schemas, improving query performance and reducing Snowflake compute costs.
- Implemented automated data quality checks using SQL-based dbt tests and the Great Expectations framework to detect anomalies and enforce data correctness before production loads.
- Orchestrated ETL workflows in Airflow using Python and managed code deployments via Git with CI/CD best practices to increase deployment reliability and maintain pipeline uptime.
- Built interactive Power BI dashboards and curated datasets to enable data-driven decision-making for stakeholders.
- Maintained technical documentation in Confluence for ETL workflows, and led knowledge-sharing sessions for new joiners.
Enrico Goerlitz
Data & AI Engineering | Backend Software Development
Last position:
Freelance Software & Data/AI Engineer at Freiberuflicher Software & Data/AI Engineer
- Lecturer for the GenAI Track at the Master School Institute of Technology
- Development of a full-stack AI application (React + Python/FastAPI) for automated supplier product import with intelligent column and category classification (4-layer hierarchical) including human-in-the-loop validation
Enrico Goerlitz
Data & AI Engineering | Backend Software Development
Last position:
Freelance Software & Data/AI Engineer at Freiberuflicher Software & Data/AI Engineer
- Lecturer for the GenAI Track at the Master School Institute of Technology
- Development of a full-stack AI application (React + Python/FastAPI) for automated supplier product import with intelligent column and category
- Lecturer for the GenAI Track at the Master School Institute of Technology
- Development of a full-stack AI application (React + Python/FastAPI) for automated supplier product import with intelligent column and category classification (4-layer hierarchical) including human-in-the-loop validation
classification (4-layer hierarchical) including human-in-the-loop validation
Vili Dhamo
Senior Data Engineer, Data Architect, Software Engineer
Last position:
Technical Lead, Data Engineer at Mercedes-Benz Consulting
- Optimized the data architecture (medallion) to better decouple processing stages and improve transparency and reproducibility
- Ensured technical quality of data processing in Databricks by introducing schema enforcement, data quality checks and a structured data architecture
- Orchestrated pipelines with Azure Data Factory
- Professionalized and automated the development and deployment process by integrating Git and GitHub Actions
- Led the Data Engineering team (3 members) in a functional role
- Conducted workshops to optimize and stabilize the data platform and the development process
- Collected and prioritized new requests, maintained the product backlog
- Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS SharePoint, Mural
Vili Dhamo
Senior Data Engineer, Data Architect, Software Engineer
Last position:
Technical Lead, Data Engineer at Mercedes-Benz Consulting
- Optimized the data architecture (medallion) to better decouple processing stages and improve transparency and reproducibility
- Ensured technical quality of data processing in Databricks by introducing schema enforcement, data quality checks and a structured data architecture
- Orchestrated pipelines with Azure Data Factory
- Optimized the data architecture (medallion) to better decouple processing stages and improve transparency and reproducibility
- Ensured technical quality of data processing in Databricks by introducing schema enforcement, data quality checks and a structured data architecture
- Orchestrated pipelines with Azure Data Factory
- Professionalized and automated the development and deployment process by integrating Git and GitHub Actions
- Led the Data Engineering team (3 members) in a functional role
- Conducted workshops to optimize and stabilize the data platform and the development process
- Collected and prioritized new requests, maintained the product backlog
- Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS SharePoint, Mural
- Professionalized and automated the development and deployment process by integrating Git and GitHub Actions
- Led the Data Engineering team (3 members) in a functional role
- Conducted workshops to optimize and stabilize the data platform and the development process
- Collected and prioritized new requests, maintained the product backlog
- Technologies: Microsoft Azure (Data Lake, Data Factory), Databricks, Apache Spark (PySpark), Python, SQL, Git, Confluence, Power BI, Power Apps, Dataverse, MS SharePoint, Mural
Christian Richter
Freelance Data Engineer
Last position:
Freelance Data Engineer at Ingenieurbüro Christian Richter – Data, Cloud & Container
- Contributed to over 20 successful projects
Christian Richter
Freelance Data Engineer
Last position:
Freelance Data Engineer at Ingenieurbüro Christian Richter – Data, Cloud & Container
- Contributed to over 20 successful projects
- Contributed to over 20 successful projects
Dimitar Stefanovski
Consultant - Senior Data Engineer (Data Architect)
Last position:
Consultant - Senior Data Engineer (Data Architect) at Seerene GmbH
- Consulted development team for data reorganization to improve performance and reduce code complexity
- Redesigned database tables for caching data and included predefined models serving client requests
- Supported product analyzing git commits to bring KPIs to managers of large engineering teams
Dimitar Stefanovski
Consultant - Senior Data Engineer (Data Architect)
Last position:
Consultant - Senior Data Engineer (Data Architect) at Seerene GmbH
- Consulted development team for data reorganization to improve performance and reduce code complexity
- Redesigned database tables for caching data and included predefined models serving client requests
- Consulted development team for data reorganization to improve performance and reduce code complexity
- Redesigned database tables for caching data and included predefined models serving client requests
- Supported product analyzing git commits to bring KPIs to managers of large engineering teams
- Supported product analyzing git commits to bring KPIs to managers of large engineering teams
Eric Ndengang Foyet
Data Engineer
Last position:
Data Engineer at Creditsafe Deutschland GmbH
Eric Ndengang Foyet
Data Engineer
Last position:
Data Engineer at Creditsafe Deutschland GmbH
Discover over 15,000 top freelancers
Data Engineers statistics
Aggregated from the professional profiles of matched freelancers.
Experience
16 years
Position duration
2.8 years
Positions per freelancer
8
Top business areas
Business Intelligence, Information Technology, Project Management
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
89%
Master's degree or higher
44%
Doctorate
11%
Certifications per freelancer
3
Most common languages
German, English, Russian
Speak two or more languages
100%
Daily Rate Distribution
The chart shows how the daily rates of freelancers in this role are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Average rates for Data Engineers & Seniority distribution
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Frequently Asked Questions
Questions in mind? Get key insights about FRATCH
A Data Engineer builds and maintains the pipelines that move data from source systems into warehouses, lakes, or BI-ready layers. The work often includes ingestion, transformation, testing, orchestration, and monitoring. Good freelancers also document the flow so the client team can keep operating it after handover.
Look for strong SQL, Python, and data modeling skills, plus experience with orchestration and cloud platforms. A solid Data Engineer should also understand data quality, logging, and version control. If the project includes streaming or large-scale processing, ask about Spark or Kafka experience as well.
A data analyst works mainly on insights and reporting, while a Data Engineer focuses on the systems that make data reliable and available. An analytics engineer sits closer to the warehouse layer and often works on models for BI consumption. In practice, these roles overlap, but the data engineer owns the plumbing and platform side.
A freelancer makes sense when the work is time-bound, urgent, or tied to a specific platform change. Many companies hire a Data Engineer for a warehouse migration, a broken pipeline, or to add capacity while a permanent search is still open. It is also useful when you need specialist skills for a narrow part of the stack.
Yes, most of the work can be done remotely if system access, ticketing, and communication are set up well. Berlin-based clients often still want an on-site start for architecture reviews, security approvals, or stakeholder alignment. Language expectations depend on the team, but English is common in technical delivery.
An ETL developer or data pipeline engineer should deliver working pipelines, transformation logic, tests, and monitoring. You should also expect documentation, handover notes, and clear ownership of failure handling. If the scope is bigger, the freelancer may also define the target data model or improve the warehouse structure.
Ask for examples of past pipelines, migration work, and how they handled broken data or changing source systems. A strong Data Engineer can explain trade-offs clearly, not just name tools. You should also check whether they think about maintainability, alerts, and how other teams will use the data.
In Berlin, Data Engineers are often brought into SaaS, product, e-commerce, and digital platform teams. Common projects include cloud warehouse setups, event tracking, API integrations, and making BI data more reliable. Mixed remote teams are normal, so clear communication matters as much as technical skill.
The average hourly rate for Data Engineers in Berlin is 84 €, which corresponds to a daily rate of about 669 € based on an 8-hour working day.
Of the freelancers working as Data Engineers in Berlin, 89% hold at least a Bachelor's degree, 44% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers working as Data Engineers in Berlin have 16 years of professional experience, with a single engagement typically lasting around 2.8 years.
The most common languages among freelancers working as Data Engineers in Berlin are German (100%), English (100%), and Russian (22%).
The most common industries among freelancers working as Data Engineers in Berlin are Information Technology (100%), Professional Services (44%), and Banking and Finance (33%).
The most common business areas among freelancers working as Data Engineers in Berlin are Business Intelligence (100%), Information Technology (100%), and Project Management (56%).
FRATCH Data Engineers main locations
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Request a Free Demo
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Philipp Thomaschewski
FRATCH CEO
