Apache Superset Experts in Berlin
in minutes from over 15,000 CVs with vetted, available specialistsHire experts who build Superset dashboards, SQL-driven charts, and reliable data exploration flows for BI teams. They connect warehouses, tune permissions, and shape reporting for fast decision-making, with precise matching to vetted, available freelancers.
Meet FRATCH Experts in Berlin, who have recently used Apache Superset
Dmitry Pankov
Last position:
Freelance Digital Marketing Analyst at Freelance
- Marketing Strategy: Lead the end-to-end analysis and evaluation of cross-channel marketing campaigns across the entire Customer Journey. My focus is identifying optimization potential and deriving clear, actionable recommendations that drive measurable business impact.
- Data Science & AI: Advanced predictive modeling (Churn, LTV), market basket analysis, clustering, and real-time AI-powered audience discovery utilizing RAG/LLMs.
- Marketing Analytics & Measurement: End-to-end attribution analysis, Marketing Mix Modeling (MMM), audience segmentation, conversion path analysis, and A/B testing across all major platforms.
- Data Engineering & Reporting: Designing and managing robust, multi-platform data pipelines (BigQuery, GCP) for data consolidation, automated dashboard generation, and critical API integrations.
Nitin Bhardwaj
Last position:
Financial Analytics Lead at Independent Consultant
Led FP&A tech transformation for a 9-figure business – from resolving legacy technical debt to leading AI-native EPM implementation
- Driving end-to-end FP&A transformation, from architecture redesign through EPM tool selection to rollout
- Ran evaluation of 12+ EPM platforms, from vendor negotiation to selection framework tied to long-term planning
- Diagnosed constraints in financial planning architecture, presented findings to the CFO, and secured executive mandate to redesign FP&A infrastructure from the ground up
Ashwin Parthasarathy
Last position:
Data Scientist at Mercor Intelligence
- Elevated LLM output reliability by engineering domain-specific prompts and evaluation logic, improving reasoning consistency across production language model workflows.
- Designed advanced coding benchmarks and validated solutions to strengthen training and evaluation datasets, improving model performance on technical problem-solving tasks.
- Designed and implemented automated evaluation frameworks for technical reasoning tasks; optimized LLM output reliability by 15% through rigorous prompt engineering and rubric-based benchmarking.
Bidya Bibhu
Last position:
Global Lead (Product) – Payments Platform (Risk & Data Products) at Chargebee
- Own strategy and roadmap for the payment orchestration and risk intelligence products serving enterprise subscription customers.
- Conduct deep workflow discovery and user interviews to redesign onboarding experience, resulting in 5× funnel throughput and 70% reduction in manual steps.
- Define PRDs for scalable data pipelines, fraud signals, and automation logic, improving insight accuracy and speed of decision-making by 30%.
- Partner with engineering, data, design, and security to ship 15+ enterprise features with 100% successful release quality.
- Introduce risk analytics dashboards and performance KPIs, reducing investigation time by 40% and improving visibility across teams.
- Lead prioritization of new capabilities, tech debt, and security initiatives (PCI DSS, access controls, auditability).
- Lead development of ML-based fraud detection models (regression, decision trees) to identify high-risk transactions, reducing chargebacks by 20%.
- Design end-to-end analytics dashboards (Tableau, Redshift) to visualise global risk exposure, cutting onboarding SLA from 2.4 days to 3 minutes.
- Partner with engineering and data teams to deploy scalable payment risk frameworks, enhancing compliance visibility and decision speed.
- Mentor analysts and data scientists through agile sprint cycles, embedding a data-driven culture across risk operations.
Anna Moiseeva
Last position:
Senior Product Manager / Project Lead at Keepcode
- Define and own the end-to-end product lifecycle for flagship project (web and mobile app, more than 15M total users). Lead delivery, track and analyse product metrics, data and KPIs.
- Drive roadmap planning: translate long-term product vision and product strategy, business objectives, customer needs into a prioritised backlog for cross-functional teams.
- Lead cross-functional teams using Agile methodologies: facilitate daily stand-up meetings, sprint planning, poker-planning, retrospectives, and demos; conduct feature kick-off meetings.
- Maintain clear and trust communication with stakeholders through product updates, presentations and regular reports, acting as a bridge between technical teams and business leaders.
- Apply data-driven hands-on approach with product analytics, experimentation, and customer interviews for decision-making across product development.
- Contribute to annual strategic planning with the Board by translating market dynamics, customer needs and competitive positioning into actionable product roadmap and goals.
- Increased in-app conversion by 13% and reduced average purchase time by 50% through Google Analytics implementation and UX/UI redesign.
- Reduced support workload by 60% by implementing an AI-powered support system with a knowledge base and automated Jira ticket creation.
- Reduced key client churn by 14% and increased internal project revenue by 22% YoY by building a data-driven analytics framework in Power BI.
- Optimised referral program costs by 17% and improved retention by 22%.
- Enabled global market expansion across 6+ regions by leading the design and delivery of a payment integration platform, integrating 10+ payment methods via a unified API.
Gyan Prakash
Last position:
Senior DevOps and Cloud Architect at Bosch
- Architected and operated cloud-based data and ML platforms for autonomous driving and parking systems, supporting large-scale (multi PB scale) simulation and vehicle data ingestion.
- Implemented security, compliance, and governance standards across Azure subscriptions and cloud resources.
- Managed GitHub organizations and CI/CD pipelines to improve deployment reliability and developer productivity.
- Contributed to hiring and technical interviews as part of the recruitment panel.
Discover over 15,000 top freelancers
Statistics of experts using Apache Superset
Aggregated from the professional profiles of matched freelancers.
Experience
13 years
Position duration
3 years
Positions per freelancer
6
Top business areas
Business Intelligence, Product Development, Information Technology
Top industries
Information Technology, Banking and Finance, Retail
Certification focus areas
Information Technology, Business Intelligence, Marketing
Bachelor's degree or higher
100%
Master's degree or higher
80%
Doctorate
20%
Certifications per freelancer
3
Most common languages
German, English, Hindi
Speak two or more languages
100%
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Berlin 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.
Average rates of experts in Berlin using Apache Superset
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.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
Dashboards that teams use
Apache Superset is an open-source business intelligence tool for interactive dashboards and data exploration. Companies use it to turn warehouse data into charts, filters, and shared views that help teams track operations, product use, and commercial activity. It is often called Superset.
Where it fits
It works well with modern data stacks and SQL-first workflows. Teams bring it in when they need self-service analysis on top of sources such as Snowflake, BigQuery, PostgreSQL, or Trino without building a custom reporting layer.
Typical expert work
- Connect data sources and set up datasets
- Build dashboards and chart collections
- Tune filters, access rules, and roles
- Support saved views and report delivery
- Align metrics and naming across teams
What strong specialists do
Strong Apache Superset specialists understand SQL, data modeling, and analytics UX. They design dashboards that answer real questions, keep queries efficient, and avoid confusing metric definitions. They also know when to extend Superset and when a warehouse or semantic layer should do the heavy lifting.
When companies need help
Freelance expertise helps during a new BI rollout, a migration from Looker or Metabase, or a cleanup of messy dashboards. Berlin teams often ask for remote support for setup and review, then bring someone on-site when workshop sessions with analysts or stakeholders are useful.
Ecosystem and delivery
Superset projects often involve authentication, row-level security, dbt models, and warehouse permissions. Good experts work well with data engineers, analysts, and product teams, and they document dashboard logic so other specialists can maintain it after launch.
Frequently asked questions
Curious about Apache Superset? Here are the answers that come up again and again.
Apache Superset is used for dashboards, charts, and self-service exploration on top of SQL data sources. It helps teams inspect business data without building a custom reporting app. Many companies also use Superset for internal reporting, operational monitoring, and shared metric views.
Superset is often chosen when a company wants an open-source BI layer with strong SQL support and flexible dashboarding. Compared with Tableau or Looker, it usually needs more hands-on setup but gives teams more control over the stack. Compared with Metabase, it tends to suit teams that want deeper customization and more complex analytics work.
A strong Apache Superset specialist should know SQL, data modeling, and dashboard design. Experience with warehouses, permissions, authentication, and performance tuning matters too. If the project touches dbt or a semantic layer, that background is very useful.
A small Superset setup can be handled by one specialist if the data model is already clean. More complex work needs someone who can handle access control, query performance, and dashboard governance. If several teams rely on the same metrics, you want an expert who can standardize definitions early.
Yes, most Apache Superset work can be done remotely because setup, dashboard building, and testing are usually tied to the data stack, not a physical location. For Berlin companies, on-site sessions can still help during stakeholder workshops or when aligning on reporting needs. Many teams use a mix of remote delivery and a few in-person meetings.
Review recent dashboard work, SQL depth, and experience with your warehouse and identity setup. A good Apache Superset freelancer should explain how they handle filters, roles, refreshes, and shared definitions. Ask for examples of how they keep analytics usable after launch.
Usually yes, because Apache Superset sits on top of a warehouse or database rather than replacing it. Common adjacent tools include dbt, SQL engines, cloud warehouses, and identity providers. The best specialists understand how those pieces affect performance and access.
A well-built Superset dashboard answers a clear question, loads quickly, and uses consistent metric names. It should keep filters simple, avoid clutter, and respect access rules. Good specialists also document the data source and logic so others can maintain it later.
The average hourly rate of freelancers in Berlin, Germany who have used Apache Superset in their recent projects is 66 €, which corresponds to a daily rate of about 525 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Apache Superset in their recent projects, 100% hold at least a Bachelor's degree, 80% hold at least a Master's degree, and 20% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Apache Superset in their recent projects have 13 years of professional experience, with a single engagement typically lasting around 3 years.
The most common languages among freelancers in Berlin, Germany who have used Apache Superset in their recent projects are German (100%), English (100%), and Hindi (50%).
The most common industries among freelancers in Berlin, Germany who have used Apache Superset in their recent projects are Information Technology (83%), Banking and Finance (50%), and Retail (50%).
The most common business areas among freelancers in Berlin, Germany who have used Apache Superset in their recent projects are Business Intelligence (100%), Product Development (100%), and Information Technology (83%).
Main locations of FRATCH Experts, who have recently used Apache Superset
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.
Countries:
Berlin 
Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
