SQL Developer / Database Engineer

i4DM•Millersville, MD

About The Position

Support ATLAS, the VA’s open-architected, multi-cloud enterprise data management and analytics platform. Design, maintain, integrate, and optimize SQL database structures, transformation logic, and data pipelines that ingest, condition, curate, and deliver multi-source data as secure, reusable enterprise data products. Use SQL Server, Azure Data Factory, Synapse Pipelines, Databricks, Starburst, and Azure Data Lake Service to improve data reliability, performance, and interoperability across ATLAS and connected source platforms. Troubleshoot discrepancies and ETL/ELT failures, translate business requirements into technical solutions, and help provide consistent access to trusted data supporting analytics, evidence-based decisions, and better outcomes for Veterans and their families. The role also supports secure and compliant access to enterprise data, data-quality controls, metadata management, data cataloging, reporting, and visualization. Work with data engineers, analysts, data scientists, and product teams to create consumable data products and enable Azure ML/AI services. Document technical work and participate in Agile/Scrum ceremonies and continuous improvement of ATLAS data services.

Requirements

Minimum five years of experience in database development, administration, and maintenance.
Strong experience with Microsoft SQL Server, including complex SQL queries, stored procedures, database design, indexing, optimization, and performance tuning.
Experience developing and troubleshooting data integrations, ETL/ELT processes, and SSIS packages.
Hands-on experience creating, updating, monitoring, and troubleshooting Azure Data Factory and Synapse Pipelines.
Experience with Databricks, Starburst, Azure Data Lake Service, and distributed or large-scale datasets.
Experience with Collibra for data cataloging, metadata management, or data governance.
Experience supporting Azure ML/AI services and preparing reliable data for analytics or machine-learning use cases.
Experience supporting Pyramid Analytics and Power BI visualization solutions and validating source data.
Excellent troubleshooting and root-cause analysis skills.
Ability to understand business requirements and translate them into technical specifications.
Ability to communicate technical details to non-technical users and stakeholders, with excellent written and verbal communication skills.
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.

Nice To Haves

Experience supporting federal agencies, the Department of Veterans Affairs, or other regulated environments.
Experience with enterprise data lakes, lakehouses, Delta Lake, Parquet, and multi-cloud data integration.
Experience working independently and collaboratively within Agile data-product teams.

Responsibilities

Design, install, configure, maintain, and optimize SQL database systems and related data structures supporting ATLAS.
Develop, maintain, monitor, and troubleshoot ETL/ELT workflows and data pipelines using Azure Data Factory and Synapse Pipelines.
Integrate structured and unstructured data from databases, APIs, cloud platforms, and other enterprise sources into Azure Data Lake Service.
Create and optimize complex SQL queries, stored procedures, database objects, and transformation logic for data conditioning and curation.
Use Databricks and Starburst to query, transform, and integrate distributed data across lakehouse and enterprise data sources.
Investigate data discrepancies, pipeline failures, and performance issues; perform root-cause analysis and implement durable fixes.
Apply data-quality controls and support metadata management and data cataloging using Collibra.
Monitor database and pipeline performance; perform query tuning, indexing, backup, recovery, patching, and reliability improvements.
Support secure, consistent, and compliant access to enterprise data through appropriate identity, authorization, and data-protection controls.
Collaborate with data engineers, analysts, data scientists, and product teams to create consumable data products and enable Azure ML/AI services.
Support reporting and visualization needs using Pyramid Analytics and Power BI, including validation of underlying data structures and accuracy.
Translate business requirements into technical specifications and communicate solutions clearly to technical and non-technical stakeholders.
Document database structures, data mappings, pipelines, operational procedures, and technical decisions.
Participate actively in Agile/Scrum ceremonies and support continuous improvement of ATLAS data services.