IBM DataStage Experts
matched in minutes with the power of AI from over 15,000 CVsHire experts who design, maintain, and tune DataStage jobs, integrate IBM InfoSphere DataStage with databases and files, and support ETL delivery across complex data flows. Get fast, precise matching with vetted, available freelancers.
Meet FRATCH Experts who have recently used IBM DataStage
Umut Gülac
Last position:
Data Architect at BA Technology
I am an experienced data engineer specializing in end‑to‑end data integration, cloud DWH architectures, and high‑quality, governed data products.
I delivered following projects and engagements as a freelancer.
- Data Migration of CRM System for AL-FA Objekt Service Gmbh
- Microsoft Software Resales Partnership
I am looking for freelance roles like: Freelance Data Engineer Cloud Data Warehouse Architect Data Modeling & Architecture Consultant MDM & Data Governance Specialist BI & Analytics Developer
Technical Focus Areas
- Data Engineering & Integration: SQL Server/SSIS, Informatica PowerCenter/IDQ, Talend, Kafka, Azure Data Factory – Delta/CDC/ELT patterns, robust pipelines, monitoring/recovery, data lineage & impact analysis, medallion architecture Bronze/Silver/Gold layers
- DWH & Cloud: Azure SQL / Data Lake / Synapse, AWS Redshift/S3, on‑prem SQL/Oracle – scalable data marts with a strong cost/benefit focus.
- Data Modeling: Atomic (Inmon) and Dimensional (Kimball), Data Vault (Linstedt), Domain‑Driven Design, clear lineage & contracts.
- MDM & Governance: Informatica MDM, IBM MDM, stewardship processes, data quality rules, survivorship/XREF, catalog/glossary, SIF/BES/REST publication.
- Analytics/BI: Power BI, SSAS, Cognos – business‑ready, maintainable data products.
Birgit Stünkel
Last position:
Business Analysis, Requirements Engineer at BMW
Refinement of epics and user stories to achieve a higher degree of automation in CRM usage. Testing of new Discountsystem
Mario Techera
Last position:
Project Lead/Manager / Consultant at all-BI GmbH
- Establishing the Microsoft Fabric platform with the company as the central data warehouse and reporting system.
- The company migrated several operational systems including D365 to new version. The new data warehouse is based on a Fabric/Power BI architecture with Azure cloud Entra Authentication.
Tasks Performed:
- Full administrative responsibility for the Fabric platform F64 and F32 capacities, as well as two F8 capacities for development and prototyping.
- Integration of Fabric with Microsoft Entra.
- Data modeling for the data warehouse bronze, silver and gold layers using data modeling tools.
- Star Schema as well as entity relationship modeling.
- Data modeling for data marts and for dimensional modeling and Power BI (semantic model).
- Design of data models for Microsoft SSAS multidimensional and tabular OLAP cubes using DAX and MDX.
- Definition of design patterns for the ETL team for loading OLAP cubes (Tabular and MD), star schemas and data vault structures.
- Planning and managing team of 4 ETL and reporting developers.
- Performance Tuning of Power BI reports, particularly the semantic layer, as well as the Fabric notebooks
- SQL Performance Tuning.
- DB Design for Azure SQL.
- Reporting directly to project senior management.
Label: Power BI, Fabric, Analysis Services (multidimensional and tabular), D365, SSIS, Tabular Editor, SQL Server and Azure SQL, TOAD Data Modeler, DBSchema, Visual Studio Code, DAX Studio, SSMS, Visual Studio, Jira and Confluence.
Ulm Paunel
Last position:
DataStage ETL Expert at ING Bank
- Datastage 11.7, dbt, Oracle 19, Python 3.12 / PySpark 3.5, Azure GitHub, Azure DevOps, Automic
- Development of migration jobs to transfer data from the collection DWH to the new Risk Mart, as well as development of ETL pipelines to migrate historical data from the old Mart to the new Risk Mart.
- Storage of the silver layer on Hadoop and the gold layer in Oracle.
- Translation of DataStage jobs into dbt to publish reporting data in Google Cloud to a PostgreSQL database.
- Creation and optimization of complex SQL queries for data extraction from a data vault, taking into account historical data in the point-in-time tables.
- Creation of Oracle table definitions (DDL) and adjustment of existing stored procedures.
- Versioning changes in GitHub and deployment via the CI/CD portal.
- Refactoring long-running DataStage jobs into Python using PySpark to reduce server load.
- Migration of SAS scripts to PL/SQL, including new development of distribution functions that have no direct equivalent in Oracle.
- Development of Automic jobs to run DataStage pipelines and Python scripts (PySpark jobs) that control the population of the SME and institutional risk tables in the Risk Mart and perform business calculations.
- Participation in the agile process, including creating user stories, estimations, and planning in Azure DevOps.
- Handling Azure DevOps tickets and close collaboration with testers and business teams for error analysis and resolution.
Peter Brungs
Last position:
Data Warehouse Consultant (Development and Analysis) at Atruvia AG
- Developed and enhanced ETL loading jobs with IBM DataStage and optimized SQL in an IBM DB2 environment as part of the Agree21 data migration
- Analyzed data quality and developed test procedures
- Created PowerShell scripts and documented GIT deployment processes
- Technologies: RedHat Linux, IBM DB2 with DBVisualizer, IBM InfoSphere DataStage 11.7, JIRA, TortoiseGIT, TortoiseSVN, PowerShell scripts
Alexander Bulgakov
Last position:
Test Manager, Test Analyst, Test Automation Engineer at Alexander Bulgakov IT-Consulting
- Managing two teams as a test manager
- Designing and conducting manual tests
- Designing, implementing, and running automated Cucumber and Tavern tests
- Creating and maintaining test plans
- Preparing and presenting execution results at iteration transitions
- Reviewing requirement tickets and related documentation
- Regular reporting and creating bug tickets
- Participating in Scrum meetings for both teams
- Supporting QA and representing QA in cross-team end-to-end test phases, meetings, and presentations
Methods & Tools:
- Tavern testing with Python
- IntelliJ with Cucumber
- Gherkin in JIRA
- various tools for handling JSON, XML, CSV, and HTML
- Insomnia for API requests
Ammad Tarar
Last position:
Senior Data Architect at Makerverse
- Designed and implemented the company's end-to-end data architecture, including ingestion, modeling, and BI layers.
- Developed modular and reusable dbt models to support product, finance, and marketing analytics.
- Introduced data governance practices and metadata management, improving trust and discoverability across teams.
Matthias Scherer
Last position:
IBM InfoSphere DataStage Senior Consultant at KKH (Kaufmännische Krankenkasse Hannover)
- Data migration from BVS to BITMARCK 21c|ng
- Test case creation; test execution and result analysis of the ETL processes
- Consulting on detailed planning and test execution
- Job review
- Development
- Documentation
- Error analysis & fixing / new development
- System environment: Windows 10; IBM InfoSphere DataStage 11.7.x; IBM DB2 z/OS; IBM DB2 LUW; PL/SQL; SQL; DBeaver 25.x; MS Office 365; Atlassian JIRA
Discover over 15,000 top freelancers
Statistics of experts using IBM DataStage
Aggregated from the professional profiles of matched freelancers.
Experience
25 years
Position duration
2 years
Positions per freelancer
18
Top business areas
Information Technology, Business Intelligence, Quality Assurance
Top industries
Information Technology, Banking and Finance, Insurance
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
86%
Master's degree or higher
57%
Doctorate
14%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100%
Based on our profile pool as of 6 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology 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 using IBM DataStage
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 6 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What it does
IBM DataStage is an ETL and data integration tool for moving, cleansing, and transforming data between systems. Teams use it to build batch pipelines, load warehouses, and standardize data from ERP, mainframe, and cloud sources. It is often searched as DataStage or IBM InfoSphere DataStage.
Typical work
- Build and maintain ETL jobs for warehouse loads
- Map, transform, and validate source data
- Orchestrate scheduled data pipelines and dependencies
- Troubleshoot job failures and data quality issues
- Tune parallel processing for heavier workloads
Ecosystem
Strong professionals know the surrounding stack, not just the canvas. That includes DB2, Oracle, SQL Server, flat files, ODBC/JDBC sources, and scheduling tools used around DataStage in production. They also understand job parameters, stages, sequences, and how to keep flows readable for long-term support.
When to bring in help
Companies usually look for freelance support when a legacy ETL landscape needs changes, a migration is underway, or delivery is blocked by slow jobs and brittle mappings. DataStage specialists are also useful for short, focused work such as fixing a failed release, documenting flows, or extending an existing framework without breaking standards.
What strong experts deliver
Good IBM DataStage specialists write clear jobs, handle complex joins and lookups, and keep error handling practical. They think about restartability, monitoring, and maintainability from the start. The best professionals can work with both old InfoSphere installations and newer integration setups without losing control of the data logic.
Collaboration style
DataStage work often fits well in mixed teams with remote specialists and internal stakeholders. For complex source systems or sensitive data, companies may still want on-site access for discovery and handover, but much of the build and support work can be done remotely. Clear access, documented rules, and agreed testing are what make the setup work.
Frequently asked questions
Before you brief your next project: the most common questions about IBM DataStage.
IBM DataStage is used to move and transform data between systems. Companies rely on it for ETL jobs, warehouse feeds, and batch integrations where data needs to be cleaned, joined, and loaded in a controlled way.
DataStage is the name many people use today, while InfoSphere DataStage is the older IBM product name you still see in projects and search results. In practice, both usually refer to the same ETL tool and the same style of job design.
IBM DataStage is often chosen in environments that already run IBM software or need strong parallel processing for large integration flows. Compared with Informatica or SSIS, the main difference is usually the surrounding stack, team skills, and how much legacy logic already exists.
A strong DataStage specialist usually brings solid SQL, data modelling, and source-to-target mapping skills. Knowledge of databases, file formats, scheduling, and basic performance tuning is important because the tool sits in the middle of many moving parts.
IBM DataStage work ranges from simple job maintenance to complex redesigns. Small fixes may only need a focused specialist, while migration, performance tuning, or framework work usually needs someone who has seen several production landscapes and understands the impact of each change.
Yes, DataStage support is often remote because the work is mostly job design, troubleshooting, and coordination through shared environments. On-site time can still help when source systems are sensitive, access is restricted, or the team needs a detailed handover with operations.
Look for clear job structure, sensible use of stages, strong error handling, and an explanation of why the flow is built that way. A good IBM DataStage expert also documents dependencies, restart points, and test cases so the solution is easy to support after handover.
The usual issues are unclear source rules, poor naming, weak dependency handling, and jobs that become hard to change over time. An experienced DataStage freelancer prevents that by keeping transformations explicit, checking data quality early, and designing for support, not just for first release.
The average hourly rate of freelancers who have used IBM DataStage in their recent projects is 93 €, which corresponds to a daily rate of about 747 € based on an 8-hour working day.
Of the freelancers who have used IBM DataStage in their recent projects, 86% hold at least a Bachelor's degree, 57% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers who have used IBM DataStage in their recent projects have 25 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers who have used IBM DataStage in their recent projects are German (100%), English (100%), and French (63%).
The most common industries among freelancers who have used IBM DataStage in their recent projects are Information Technology (100%), Banking and Finance (75%), and Insurance (75%).
The most common business areas among freelancers who have used IBM DataStage in their recent projects are Information Technology (100%), Business Intelligence (88%), and Quality Assurance (88%).
Main locations of FRATCH Experts, who have recently used IBM DataStage
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
