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Databricks Migration Engineer (Remote)

Tier One Technologies, LLC

Role overview

Qualifications

  • Bachelor's degree or higher from an accredited college or university in Computer Science, Engineering, or a related technical field.
  • 5+ years of experience in Data Engineering, Data System Development or related roles.
  • 5+ years of experience with Cloud platforms (e.g. Azure, AWS, GCP).
  • 1+ year leading complex, cross-functional data projects and technical teams.

Responsibilities

  • Lead the technical migration from legacy SQL Server stored procedures and ADF pipelines to Databricks Lakehouse (Delta Lake).
  • 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.
  • Implement advanced optimization techniques, including Z-Ordering, data skipping, and materialized views.

Key facts

Hard skills

Databricks Databricks Data Engineering Oracle Adf Power BI Microsoft Azure Amazon Web Services gRPC Apache Spark Organizational Structure

Other skills

  • Communication
  • Detail Oriented

About the company

Tier One Technologies, LLC logo

Tier One Technologies, LLC

Tier One Technologies is a national technical consulting and services firm. The company provides technical delivery management for clients primarily in the government sector including Federal, State and Local. Tier One Technologies is a GSA MAS Schedule 70 contract holder.

Company details

Company size11 - 50

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Job description

Overview:
  • Tier One Technologies is seeking a Databricks Migration Engineer to support our US Government client.
  • This remote Contract-to-Hire position will be originated in Rosslyn, VA. Washington DC area and East Coast time zone candidates preferred.
  • Must be a US Citizen.
  • SELECTED CANDIDATES WITHOUT REQUIRED CLEARANCE WILL BE SUBJECT TO A FEDERAL GOVERNMENT BACKGROUND INVESTIGATION TO RECEIVE IT.
Responsibilities:
  • 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
Qualifications:
  • Bachelor's degree or higher from an accredited college or university in Computer Science, Engineering, or a related technical field.
  • 5+ years of experience in Data Engineering, Data System Development or related roles.
  • 5+ years of 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.
  • Excellent communication skills.
  • Must be a US Citizen and be able to obtain a Position of Public Trust Clearance.
  • Must have resided in the US for the last 5 years and not have traveled outside the US for a combined total of 6 months or more in last 5 years.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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