Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions.
We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.
In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing.
The project involves migration of legacy and TMS-related data into Google BigQuery as part of a broader data platform modernization initiative. The team is responsible for designing ingestion frameworks, implementing transformation pipelines, ensuring data quality, and delivering production-grade datasets for analytical consumption.
Key Technologies
Required: SQL, Data Reconciliation, Data Quality Testing, ETL/ELT Validation
Preferred: Google BigQuery, Python, BI/Reporting Testing, APIs, Data Profiling
Nice to Have: Looker, dbt, Airflow/Composer, GCP, Data Observability, Data Governance
You will be:
Strong SQL skills, including complex queries, joins, aggregations, window functions, and data comparisons
• Hands-on experience validating data across different systems, databases, or reporting platforms
• Proven experience with data quality testing, reconciliation, and validation of migrated data
• Ability to analyse discrepancies between source and target datasets and identify their root causes
• Experience validating ETL/ELT pipelines, including completeness, accuracy, consistency, and transformation logic
• Good understanding of data models, relationships, schemas, and data dependencies
• Experience testing structured and semi-structured data
• Ability to translate business and reporting requirements into test scenarios and validation rules
• Experience defining and executing data quality checks, including:
o record counts and completeness
o null and duplicate checks
o referential integrity
o field-level reconciliation
o aggregation and KPI validation
o business rule validation
o historical data consistency
• Ability to distinguish between source data issues, transformation defects, and reporting/visualisation issues
• Experience documenting defects and working closely with Data Engineers to investigate and resolve data discrepancies
• Good analytical and problem-solving skills
• Experience working with Git-based development workflows and Agile delivery teams
Your profile:
- Your experience:
• Hands-on experience with Google BigQuery
• Experience testing data migrations or reporting platform migrations
• Experience validating dashboards, reports, KPIs, and analytical datasets
• Understanding of ETL/ELT concepts and modern cloud data architectures
• Experience with automated or semi-automated data validation using SQL and/or Python
• Basic Python skills for data analysis, comparison, or test automation
• Experience with data profiling and identifying anomalies in large datasets
• Understanding of data quality dimensions such as accuracy, completeness, consistency, uniqueness, validity, and timeliness
• Experience working with APIs and validating externally sourced data
• Understanding of data lineage and the ability to trace data from source through transformations to the reporting layer
• Experience with defect management and test documentation
• Ability to work directly with business stakeholders to clarify expected reporting results and business rules Practical experience using AI-powered assistants (e.g. Claude Code, GitHub Copilot, Cursor) to improve productivity, quality, or decision-making in software delivery.
Work from the European Union region and a work permit are required.
- • Hands-on experience with Looker or another BI/reporting platform
• Experience with GCP Dataform tests or similar data testing frameworks (eg. dbt tests)
• Experience in Retail or eCommerce
• Experience with reconciliation of sales, stock, product, customer, or transactional data
• Familiarity with Airflow / Cloud Composer
• Experience with data observability or data quality tools
• Understanding of CI/CD practices for data pipelines and automated data tests
• Experience with Google Cloud Platform and its data services
• Familiarity with Data Governance, metadata management, and data cataloguing
• Experience preparing or validating datasets used for Analytics, Data Science, or Machine Learning Experience applying GenAI in a more structured way within the SDLC, including defined workflows, prompt patterns, or tool integrations embedded into daily work.
- Interest in and familiarity with emerging AI-driven practices (e.g. agent-based workflows, automation patterns, AI-augmented development), with a willingness to explore and experiment beyond standard approaches.
Recruitment Process:
CV review – HR call – Interview – Client Interview – Decision
Skills Required
- Strong SQL skills, including complex queries, joins, aggregations, window functions, and data comparisons
- Hands-on experience validating data across systems, databases, or reporting platforms
- Experience with data quality testing, reconciliation, and migrated-data validation
- Experience validating ETL/ELT pipelines and transformation logic
- Understanding of data models, relationships, schemas, and data dependencies
- Experience testing structured and semi-structured data
- Ability to define test scenarios and validation rules from business and reporting requirements
- Experience with completeness, null, duplicate, referential integrity, field-level, KPI, business-rule, and historical-consistency checks
- Ability to identify root causes of discrepancies and distinguish source issues, transformation defects, and reporting issues
- Experience documenting defects and collaborating with Data Engineers
- Experience with Git-based workflows and Agile delivery teams
- Hands-on experience with Google BigQuery
- Experience testing data or reporting-platform migrations
- Experience validating dashboards, reports, KPIs, and analytical datasets
- Understanding of ETL/ELT and modern cloud data architectures
- Experience with automated or semi-automated validation using SQL or Python
- Basic Python skills for analysis, comparison, or test automation
- Experience with data profiling and anomaly identification in large datasets
- Understanding of data quality dimensions, including accuracy, completeness, consistency, uniqueness, validity, and timeliness
- Experience working with APIs and validating externally sourced data
- Understanding of data lineage and source-to-reporting traceability
- Experience with defect management and test documentation
- Ability to work with business stakeholders to clarify reporting results and business rules
- Practical experience using AI-powered assistants such as Claude Code, GitHub Copilot, or Cursor
- Work authorization and a work permit in the European Union
- Experience with Looker or another BI/reporting platform
- Experience with GCP Dataform tests or comparable frameworks such as dbt tests
- Experience in Retail or eCommerce
- Experience reconciling sales, stock, product, customer, or transactional data
- Familiarity with Airflow or Cloud Composer
- Experience with data observability or data quality tools
- Understanding of CI/CD for data pipelines and automated data tests
- Experience with Google Cloud Platform data services
- Familiarity with data governance, metadata management, and data cataloguing
- Experience preparing or validating datasets for Analytics, Data Science, or Machine Learning
- Experience applying GenAI in structured SDLC workflows
- Familiarity with AI-driven practices such as agent-based workflows and AI-augmented development
Xebia Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Xebia and has not been reviewed or approved by Xebia.
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Healthcare Strength — U.S. offerings include health, dental, and vision insurance alongside an Employee Assistance Program, strengthening total compensation where available.
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Leave & Time Off Breadth — Vacation/PTO and paid holidays, with mentions of parental leave in certain regions, broaden time-off options and support work-life balance.
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Retirement Support — A U.S. 401(k) plan with matching is noted, enhancing long-term financial benefits as part of total rewards.
Xebia Insights
What We Do
We are a pioneering IT consultancy company, following 1 mission, 4 values, and 4 business principles. WHO WE ARE With over 20 years of experience, our global network of passionate technologists and pioneering craftsmen deliver cutting-edge technology and game-changing consulting to companies on the brink of transformation. Founded in 2001, Xebia was the first Dutch organization to embrace the Agile way of working, with gurus like Jeff Sutherland. Since then, we have grown from a Java company into a full-service digital consulting company with 4500+ professionals working on a worldwide ambition. We are organized in complementary chapters – teams with a tremendous amount of knowledge and experience within a particular field, such as Agile, DevOps, Data and AI, Cloud, Software Technology, Low Code, and Microsoft. We help the world’s top 250 companies and category leaders overcome digital challenges, embrace innovation, adopt new technology, and implement new business models. In addition to high-quality consulting, we also provide offshoring and nearshoring services. WHAT WE DO ★ Digital Strategy ★ DevOps and SRE ★ Agile ★ Data and AI ★ Cloud ★ Microsoft Solutions ★ Software Technology ★ Security ★ Low Code ★ Xebia Academy HOW WE ARE ORGANIZED Xebia has launched specific labels, like GoDataDriven, Binx, Xpirit, Qxperts, Stackstate, Instruqt, Xccelerated, and Xebia Academy Complementing our organic growth, other specialized companies join our successful journey and also operate within the Xebia network under their own brand name, like Appcino, coMakeIt, g-company, Oblivion, PGS Software, and SwissQ. Together we are Xebia. With 17 offices in Atlanta, San Francisco, UK, Vietnam, Canada, Amsterdam, and Hilversum (the Netherlands), Belgium, Germany, Gurgaon, Jaipur, Hyderabad, Pune, Bangalore, Poland, Melbourne, Mexico, and Dubai. ✉️ [email protected]
