Overview
PLEASE NOTE: No corp-to-corp candidates will be accepted.
•
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. 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.
Originally posted on Himalayas
Overview
PLEASE NOTE: No corp-to-corp candidates will be accepted.
•
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. 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.
Originally posted on Himalayas