This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
We are seeking a Senior Azure Data Engineer to help design, build, and operate our next-generation enterprise data platform on Microsoft Azure. You will own end-to-end delivery of data pipelines and data products that power analytics, regulatory reporting, operational dashboards, and emerging AI/ML use cases. You will partner closely with data architects, analytics engineers, data scientists, business stakeholders, and platform engineering teams to deliver reliable, performance, secure, and cost efficient data solutions. This role is ideal for an engineer with strong hands-on depth in Azure Data Factory, Azure Synapse Analytics and/or Databricks, and modern Lakehouse patterns, who is comfortable leading migration programs (e.g., Informatica-to-ADF, on-prem warehouse-to-cloud), mentoring mid-level engineers, and shaping engineering standards across the team.
Job Responsibility
Design and build robust, reusable, parameter-driven ingestion and transformation pipelines using Azure Data Factory, Synapse Pipelines, Data Bricks and/or Microsoft Fabric Data Factory
Implement medallion architecture (Bronze / Silver / Gold) on Azure Data Lake Storage Gen2 using Delta Lake, Parquet, and structured streaming patterns
Build performant ELT workflows that leverage pushdown to source systems (Synapse Dedicated SQL Pool, Azure SQL, Teradata) where appropriate
Develop and optimize PySpark notebooks and jobs on Azure Databricks or Synapse Spark
Design dimensional models (Kimball star/snowflake) and data vault patterns for analytics consumption
Implement Slowly Changing Dimensions (Type 1/2/3), Change Data Capture, and late-arriving data patterns
Tune distributed SQL workloads in Synapse Dedicated SQL Pool / Fabric Warehouse, including distribution keys, partitioning, and clustered column store indexes
Implement CI/CD for data pipelines using Azure DevOps (YAML pipelines, ARM/Bicep/Terraform) across Dev / SIT / UAT / Prod environments
Instrument pipelines with robust logging, auditing, and monitoring using Azure Monitor, Log Analytics, and KQL
Define and enforce coding standards, code review practices, branching strategies, and release management
Lead or contribute to legacy-to-cloud migrations — e.g., Informatica PowerCenter to Azure Data Factory, on-premises Teradata / Oracle / SQL Server to Synapse or Fabric
Perform workload assessment, capacity planning, and cost modeling for target-state architectures
production incident response for critical pipelines
Requirements
Deep hands-on expertise with Azure Data Factory: pipelines, datasets, linked services, triggers, parameterization, mapping data flows, and all three Integration Runtime types (Azure, Selfhosted, SSIS)
Strong Experience in Data Bricks and PySpark
Production experience with one or more of: Azure Synapse Analytics (Dedicated and Serverless SQL Pools, Spark Pools) OR Azure Databricks (Delta Lake, Unity Catalog) OR Microsoft Fabric (Warehouse, Lakehouse, OneLake)
Strong working knowledge of Azure Data Lake Storage Gen2 (hierarchical namespace, RBAC + ACLs, lifecycle management, security)
Experience with Azure Key Vault, Azure AD / Entra ID (including managed identities and service principals), and private networking (VNet integration, private endpoints)
Monitoring and troubleshooting with Azure Monitor, Log Analytics, and KQL