ECS

Senior Databricks Migration Engineer

ECS$130K — $158K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related field.
  • 5+ years in data engineering or development roles.
  • 5+ years experience with cloud platforms such as Azure, AWS, or GCP.
  • 1+ year leading cross-functional data projects and technical teams.
  • Hands-on experience with Databricks Lakehouse and Apache Spark.

Responsibilities

  • Lead migration efforts from legacy SQL systems to Databricks Lakehouse.
  • Translate relational data warehousing to scalable Lakehouse frameworks.
  • Design ETL/ELT frameworks using PySpark and Databricks tools.
  • Architect the Gold Layer for optimal Power BI performance.
  • Optimize Databricks SQL Warehouses for low-latency queries.
  • Implement advanced optimization techniques within Databricks.
  • Define governance standards for cluster sizing and SQL compute resources.
  • Create monitoring dashboards to track DBU consumption and costs.
  • Establish data security models using Unity Catalog for governance.
  • Act as the primary technical lead and coach team members.
  • Develop comprehensive technical documentation for migration.

Benefits

  • Health, dental, and vision insurance.
  • Retirement and savings plan options.
  • Generous paid time off policy.
  • Professional development opportunities.
  • Flexible work environment with hybrid options.
Full Job Description
ECS is seeking a Senior Databricks Migration Engineer to work onsite for the US Postal Services' Inspector General's Office (OIG) at our Arlington, VA office. This role leads technical data migration efforts from legacy SQL systems, warehouses and servers to Databricks Lakehouse (Delta Lake), ensuring best practice Lakehouse design. This also includes building large data structures and dashboards and reporting on data migration projects.

Responsibilities include:
  • Lead the technical migration from legacy SQL Server stored procedures and ADF pipelines to Databricks Lakehouse (Delta Lake), ensuring best practice Lakehouse design.
  • Translate traditional relational data warehousing paradigms into scalable, distributed Lakehouse frameworks (Bronze, Silver, Gold).
  • Design robust, reusable ETL/ELT frameworks using PySpark, Delta Live Tables (DLT), and Databricks Workflows.
  • Architect and refine the Gold Layer (dimensional models, star schemas) specifically to maximize Power BI performance.
  • Optimize Databricks SQL Warehouses to support high-concurrency, low-latency Power BI queries (DirectQuery and Import modes).
  • Implement advanced optimization techniques, including Z-Ordering, data skipping, liquid clustering, and materialized views.
  • Define and enforce governance standards for cluster sizing, auto-scaling policies, and serverless SQL compute to balance performance with cost.
  • Implement proactive monitoring dashboards to track Databricks Unit (DBU) consumption and identify cost-saving opportunities.
  • Establish best practices for partition strategies and file size management within Delta Lake.
  • Design and implement a robust data security model using Unity Catalog for centralized governance.
  • Enforce row-level and column-level security policies to ensure compliant data access for Power BI consumers and internal analysts.
  • Align the Lakehouse security architecture with existing enterprise Azure Active Directory (Microsoft Entra ID) and RBAC standards.
  • Act as the primary technical lead, conducting dedicated pair-programming sessions, workshops, and code reviews to transition the team from SQL-centric to Spark-centric thinking.
  • Create comprehensive technical documentation, including architecture diagrams, design patterns, and optimization playbooks.
  • Build a foundational knowledge transfer framework to ensure the internal team is fully self-sufficient post-migration.
  • Communicate effectively verbally and in written form to both technical and non-technical audience
  • Work in an organized fashion, completing tasks timely while paying close attention to details

Please Note: This position is contingent upon additional funding and requires a Public Trust background investigation. This entails an in-depth background check & either US Citizenship or Permanent Resident (Green Card) status.

  • Bachelor's degree or higher from an accredited college or university in Computer Science, Engineering, or a related technical field
  • 5+ years' experience in data engineering, data system development or related roles
  • 5+ years' experience with cloud platforms (e.g. Azure, AWS, GCP)
  • 1+ year leading complex, cross-functional data projects and technical teams
  • Experience with Databricks Lakehouse, Apache Spark, Delta Lake, cloud-native databases, storage solutions, and distributed compute platforms
  • Experience with data warehousing, dimensional modeling, enterprise data lakes, incremental data loads, and metadata-driven ingestion and data quality frameworks using PySpark

Note: This position requires working onsite 4 days a week at out USPS customer site in Arlington, VA.

Salary Range: $130,000 - $158,000 annually

General Description of Benefits

About ECS

ECS is a leading provider of digital solutions and services to the federal government. The company was founded in 2001 by Roy Kapani and has since grown to become a trusted partner to a wide range of government agencies. ECS offers a broad range of services, including cloud computing, cybersecurity, and artificial intelligence. The company has been recognized for its innovative solutions and has won numerous awards, including the AWS Public Sector Partner of the Year award.
Learn more about ECS
Size
2,000 employees
Industry

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