Enterprise Data Warehouse (EDW) ETL/Data Engineer

CSpring

$100K — $130K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of enterprise data warehouse or data engineering experience
  • 5+ years of data modeling experience using ERWIN or similar tools
  • Deep expertise in Azure Data Factory and its various components
  • Strong experience with Azure Databricks and PySpark
  • Comprehensive understanding of Azure Data Lake Storage Gen2 and its features
  • Advanced SQL proficiency, including optimization and performance tuning
  • Strong Python skills for data engineering tasks.

Responsibilities

  • Lead the design and development of data ingestion and transformation pipelines
  • Construct medallion architecture solutions with Azure Data Lake and structured streaming
  • Create efficient ELT workflows for various Azure platforms
  • Develop and optimize PySpark notebooks for distributed processing
  • Design and implement dimensional data models and data vault patterns
  • Establish CI/CD processes for data pipelines with Azure DevOps
  • Drive cloud modernization initiatives, particularly in migrating from on-premise systems to Azure.

Benefits

  • Collaborative work environment with cross-functional teams
  • Exposure to advanced Azure data technologies and methodologies
  • Opportunities for professional growth and skill enhancement
  • Engagement in impactful enterprise-level data projects
  • Work on the cutting edge of cloud data engineering and AI/ML initiatives.
Full Job Description
We are seeking a Senior Azure Data Engineer to help design, build, and support a next-generation enterprise data platform on Microsoft Azure. In this role, you will lead the development of scalable data pipelines and data products that power analytics, operational reporting, dashboards, and emerging AI/ML use cases.

You'll work closely with data architects, analytics engineers, data scientists, platform teams, and business stakeholders to deliver secure, high-performing, and cost-effective cloud data solutions. This role is ideal for someone with deep hands-on experience in Azure data technologies, modern Lakehouse architectures, and enterprise-scale data migrations.

What You'll Do

Data Pipeline Engineering
  • Design and develop reusable, parameter-driven ingestion and transformation pipelines using Azure Data Factory, Synapse Pipelines, Databricks, and/or Microsoft Fabric Data Factory
  • Build and maintain medallion architecture (Bronze / Silver / Gold) solutions using Azure Data Lake Storage Gen2, Delta Lake, Parquet, and structured streaming patterns
  • Develop performant ELT workflows leveraging pushdown processing to platforms such as Synapse Dedicated SQL Pool, Azure SQL, and Teradata
  • Create and optimize PySpark notebooks and distributed processing jobs in Azure Databricks or Synapse Spark

Data Warehousing & Modeling
  • Design dimensional data models using Kimball star and snowflake methodologies
  • Implement data vault patterns, Slowly Changing Dimensions (Type 1/2/3), Change Data Capture, and late-arriving data strategies
  • Optimize distributed SQL workloads in Synapse Dedicated SQL Pool and/or Fabric Warehouse environments
  • Tune partitioning, indexing, and query performance for enterprise-scale datasets

Cloud Platform Engineering & DevOps
  • Implement CI/CD processes for data pipelines using Azure DevOps, YAML pipelines, ARM templates, Bicep, and/or Terraform
  • Build monitoring, logging, and auditing solutions using Azure Monitor, Log Analytics, and KQL
  • Support code reviews, branching strategies, release management, and engineering standards across environments
  • Participate in troubleshooting and production incident response for critical data pipelines

Migration & Modernization
  • Lead or contribute to cloud modernization initiatives, including Informatica PowerCenter to Azure Data Factory migrations
  • Support migration efforts from on-premises Teradata, Oracle, or SQL Server environments to Azure Synapse or Microsoft Fabric
  • Assist with workload assessments, capacity planning, and cloud cost optimization initiatives


Requirements

What You Bring

Required Qualifications
  • Deep hands-on expertise with Azure Data Factory, including pipelines, datasets, linked services, triggers, parameterization, mapping data flows, and Integration Runtime types (Azure, Self-hosted, and SSIS)
  • Strong experience with Azure Databricks and PySpark
  • Production experience with one or more of the following:
    • Azure Synapse Analytics (Dedicated SQL Pools, Serverless SQL Pools, Spark Pools)
    • Azure Databricks (Delta Lake, Unity Catalog)
    • Microsoft Fabric (Warehouse, Lakehouse, OneLake)
  • Strong understanding of Azure Data Lake Storage Gen2, including hierarchical namespace, RBAC/ACL security, lifecycle management, and governance
  • Experience with Azure Key Vault, Azure AD / Entra ID, managed identities, service principals, and private networking concepts
  • Experience monitoring and troubleshooting data solutions using Azure Monitor, Log Analytics, and KQL
  • Advanced SQL skills including window functions, CTEs, query optimization, execution plan analysis, and performance tuning
  • Strong Python skills for data engineering, including pandas, PySpark, REST API integration, and unit testing with pytest
  • Proficiency with T-SQL and familiarity with Spark SQL, KQL, PowerShell, and Bash scripting


Preferred Qualifications
  • 5+ years of enterprise data warehouse or data engineering experience
  • 5+ years of data modeling experience using ERWIN or similar modeling tools
  • 2+ years of experience with Azure Data Factory and Snowflake
  • Experience working in healthcare or Medicaid environments

If you're passionate about modern cloud data engineering and want to work on impactful enterprise initiatives, we'd love to hear from you.Source role provided by user: ?filecite?turn0file0?L1-L46?

Similar Jobs

More Jobs at CSpring

More Information Technology Jobs

Find similar Enterprise Data Warehouse (EDW) ETL/Data Engineer jobs: