Azure Databricks Data Engineer

Title: Azure Databricks Data Engineer
Location: Saint Louis MO-Day 1 Onsite
Duration: Full Time/Permanent Role
Salary Range: $110000-$135000 Per Year Benefits

Must Have Technical/Functional Skills

• Significant data engineering experience including substantial hands-on Databricks development experience.
• Azure Databricks - Strong hands-on experience building production-grade batch pipelines and lakehouse solutions.
• PySpark / Spark SQL - Advanced transformations joins window functions reusable frameworks debugging and performance tuning.
• Delta Lake - Table design schema evolution merge/upsert patterns Eligible to workimization data reliability and history management.
• Medallion architecture - Practical delivery experience across source-aligned conformed and consumption-ready layers.
• Data modeling - Fact/dimension design conformed dimensions slowly changing dimensions aggregates and semantic-consumption considerations.
• Data quality and testing - Profiling rule implementation reconciliation unit/integration tests controls and defect analysis.
• Azure ecosystem - Working knowledge of Azure Data Lake Storage and relevant Azure integration identity monitoring and DevOps services.
• DevOps - Git-based development code reviews CI/CD environment promotion release controls and automated deployment.
• Security/governance - Experience implementing least-privilege access and working with catalog lineage classification and row-level security requirements.
• SQL - Advanced SQL development and query Eligible to workimization for large analytical datasets.
• Hands-on exposure to Databricks Lakeflow Spark Declarative Pipelines or Delta Live Tables and the ability to adEligible to work evolving Databricks-native pipeline standards.
• Experience with Unity Catalog; familiarity with enterprise data-governance and data-quality tooling such as Informatica.
• Experience with HR data from Workday Dayforce PeopleSoft recruiting workforce management or talent systems.
• Understanding of Power BI consumption patterns star schemas refresh needs aggregates and performance requirements.
• Experience creating accelerators reusable engineering templates metadata-driven pipelines or automated test frameworks.
• Databricks Data Engineer certification or equivalent cloud/data engineering credential.
• Experience in a blended onshore/offshore Agile delivery model.

Roles & Responsibilities

• Design and develop scalable batch data pipelines in Azure Databricks using PySpark and Spark SQL.
• Build and maintain bronze silver and gold data structures including certified fact and dimension data products.
• Translate business metric definitions calculation rules filters granularity history and refresh requirements into technical designs.
• Create reusable transformations for HR domains such as retention hiring transfers promotions reviews hours and scheduling.
• Implement data-quality checks reconciliation exception handling auditability lineage and technical documentation.
• Eligible to workimize Spark workloads Delta tables joins partitions file sizes and cluster usage for performance and cost.
• Apply enterprise security and governance standards including Unity Catalog integration permissions sensitive-data handling and support for row-level access patterns.
• Coordinate with ingestion data governance modeling DevOps and Power BI teams to define clear data contracts and acceptance criteria.
• Contribute to CI/CD source control automated testing deployment operational monitoring and production-readiness activities.
• Participate in requirement workshops and explain technical choices clearly to business HR analytics and engineering stakeholders.
• Support knowledge transfer and mentor participating engineers or analysts

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Required Experience:

IC