Senior Azure Data Engineer

Poland and Central-Eastern Europe; United States; Remote; USD 123,000 - 167,000; Full time

Job summary

Xebia is a global AI-first, digital transformation and engineering partner. We seek a data platform engineer to shape Azure-based data platforms using Databricks, Medallion architecture, and Delta Lake, building robust ingestion pipelines.

You will work with architects, engineers, and EU clients to define data requirements, governance, CI/CD, dbt models, and Power BI/Microsoft Fabric integrations.

Qualifications

• Designing data platforms in Azure with Databricks.
• Knowledge of Medallion Architecture and Delta Lake.
• Strong SQL and data modelling skills.
• Experience creating ingestion/transformation pipelines across source systems.
• Background in data profiling, governance and quality controls.
• Practical dbt knowledge and engineering best practices.
• Ability to document technical designs and standards.
• Excellent communication and stakeholder management.
• Ability to estimate engineering effort and identify risks.
• Familiarity with Power BI and Microsoft Fabric ecosystems.

Responsibilities

• Design Azure-based data platforms with Databricks.
• Profile sources (HR/payroll/finance) and define data requirements.
• Define data ingestion and transformations (Bronze/Silver/Gold).
• Document designs, ensure governance and quality controls.
• Collaborate with architects, engineers and clients in workshops.
• Develop CI/CD practices for analytics pipelines.
• Size and estimate delivery effort and risks.
• Present technical findings to stakeholders.

Skills

Azure Databricks expertise

Medallion architecture

SQL and data modelling

End-to-end ingestion pipelines

Data governance & quality controls

dbt

Documentation & engineering standards

Stakeholder collaboration

Estimating effort & risk management

Power BI / Microsoft Fabric knowledge

Tools

Azure Databricks

Delta Lake

dbt

Power BI

Microsoft Fabric

Azure Data Factory

Job description

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 Millennium, ING, Play, Edenred, Arabian Drilling, FedEx, Leroy Merlin, Truecaller, Volotea, Schmitz Cargobull, 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.

You will be:

• Mapping candidate-to-cash business processes to the underlying source systems.
• Profiling ATS, payroll, finance, HR and other relevant platforms to assess available data and its quality.
• Identifying data quality issues, integration challenges and data governance requirements.
• Defining data requirements for complex recruiter cost-allocation processes.
• Designing data ingestion and transformation pipelines using Azure Databricks and the Bronze, Silver and Gold layers.
• Preparing technical design documentation and engineering standards.
• Defining dbt project structures, testing approaches, naming conventions and CI/CD practices.
• Assessing the feasibility of requested KPIs by validating data availability and quality.
• Providing technical assumptions and sizing inputs for delivery-phase estimates.
• Identifying technical risks, dependencies and data-related constraints.
• Collaborating with architects, platform engineers, business stakeholders and the client’s technical teams.
• Participating in workshops, architecture reviews and design validation sessions.

Your profile:

• Strong experience designing data platforms in Azure, with hands-on expertise in Azure Databricks.
• A solid understanding of Medallion Architecture and modern data lake architectures, including Delta Lake.
• Strong SQL and data modelling skills.
• Experience designing ingestion and transformation pipelines across multiple source systems.
• Background in source system analysis, data profiling and data quality assessment in large-scale enterprise environments.
• Experience defining data integration strategies across HR, payroll, finance or operational systems.
• Practical knowledge of dbt and data engineering best practices.
• Understanding of data governance, lineage, testing and quality controls.
• Experience documenting technical designs and engineering standards.
• Familiarity with Microsoft Fabric and Power BI ecosystems.
• The ability to estimate engineering effort and identify technical risks and dependencies.
• Strong communication, analytical and problem-solving skills.
• Confidence facilitating technical discussions and workshops with both technical and business stakeholders.
• Independence and a structured approach to work in a consulting environment.
• Excellent documentation skills and the ability to translate business requirements into technical solutions.

Work from the European Union region and a work permit are required.

Nice to have:

• Experience with Azure Data Factory, Unity Catalog or Microsoft Entra ID.
• Knowledge of data security and access segregation models.
• Experience implementing CI/CD for analytics platforms.
• Familiarity with recruitment, staffing, HR, payroll or finance datasets.
• Experience designing KPI and reporting data models.
• Involvement in data platform roadmaps or estimation activities.
• Previous consulting or client-facing experience, especially in Discovery & Design engagements.
• Experience presenting technical findings to technical and business audiences.
• Contributions to architecture reviews or strategic planning exercises.

Recruitment Process:

CV review – HR call – Interview – Client Interview – Decision