[Remote] Data Engineer
Note: The job is a remote job and is open to candidates in USA. MSR Technology Group is seeking a Data Engineer to design and build robust data pipelines and optimize data models. The role involves working with Azure technologies to implement data ingestion, transformation, and storage solutions while ensuring efficient data workflows and monitoring.
Responsibilities
- 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 environment
- 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
Skills
- 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
- Advanced SQL — window functions, CTEs, query optimization, execution plan analysis, performance tuning
- Strong Python for data engineering — pandas, PySpark, REST API integration, unit testing (pytest)
- Proficient in T-SQL; familiarity with Spark SQL, KQL, PowerShell, and Bash shell scripting
- 5+ years of data warehouse development experience
- 5+ years of data modeling experience using ERWIN or similar tools
- 2+ years of experience with Azure Data Factory and Snowflake
- Medicaid Domain Knowledge is a plus
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