RT

Enterprise Data Warehouse (EDW) ETL/Data Engineer

Hiring from
United States
Work type
Remote
Posted
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For over twenty-seven years RCR Technology Corporation has delivered the highest quality services to our clients with an expansive portfolio of industry-relevant services, and deep technical capabilities around data management and application development.

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.

Key Responsibilities:

Pipeline Design & Development

• 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.

Data Modeling & Warehousing

• 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.

Platform Engineering & DevOps

• 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.

Migration & Modernization

• 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.

Required Qualifications:

• Deep hands-on expertise with Azure Data Factory: pipelines, datasets, linked services, triggers, parameterization, mapping data flows, and all three Integration Runtime types (Azure, Self-hosted, 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.

Preferred Qualifications:

· 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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