DataOps Engineer

Booz Allen Hamilton•McLean, VA

14h•$62,000 - $141,000•Hybrid

About The Position

As a DataOps Engineer, you will enhance data quality, streamline data pipelines, and enable scalable cloud-based solutions supporting veterans and staff at the Department of Veterans Affairs. You will apply modern data engineering practices, automation, and cloud-native tooling to solve complex data challenges; guide architecture; build resilient pipelines; and ensure data assets are governed, discoverable, and ready for analytics and application needs across the VA. You will research current environments, industry standards, and modern DevSecOps and DataOps methodologies to recommend tools and solutions. In partnership with software engineers, product teams, architects, and stakeholders, you will develop and maintain secure, automated, and highly available data services. The role uses AWS cloud services, orchestration tools, SQL and NoSQL data stores, event streaming platforms, and CI/CD automation to design pipelines that meet mission needs. The position is hybrid and located in McLean, Virginia, with an additional location in Melbourne, Florida.

Requirements

At least 3 years of experience in data engineering or DataOps, including building scalable data pipelines and data processing solutions.
Experience designing, implementing, and maintaining ETL or ELT pipelines in cloud or hybrid environments.
Experience with MSSQL and a scripting or programming language such as Python, Bash, or Java.
Experience with modern data storage technologies, including relational databases, data lakes, or NoSQL.
Experience implementing data validation, data quality checks, and automation for data workflows.
Knowledge of version control, CI/CD practices, and automated deployment pipelines.
Ability to assess existing data systems and design integration points, ingestion patterns, and pipeline improvements.
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements.
High school diploma or GED.

Nice To Haves

Experience with Azure cloud services such as Azure Blob Storage, Azure Data Factory, Azure Functions, Azure SQL Database, Azure Synapse Analytics, Azure HDInsight, Azure Stream Analytics, or Azure Logic Apps.
Experience with workflow orchestration tools such as Azure Data Factory, Azure Logic Apps, Azure Batch, or Apache Airflow on Azure.
Experience with Infrastructure-as-Code tools such as Terraform or CloudFormation.
Experience working with containerized environments, including Docker or Kubernetes.
Experience supporting DataOps capabilities, including observability, lineage, metadata management, and pipeline monitoring.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
Cloud Practitioner, Data Engineer, or Architect certification.

Responsibilities

Enhance data quality and streamline data pipelines.
Build scalable data pipelines and data processing solutions.
Design, implement, and maintain ETL or ELT pipelines in cloud or hybrid environments.
Guide architecture and build resilient pipelines.
Ensure data assets are governed, discoverable, and ready for analytics and application needs.
Research current environments, industry standards, and modern DevSecOps and DataOps methodologies to recommend tools and solutions.
Develop and maintain secure, automated, and highly available data services in collaboration with software engineers, product teams, architects, and stakeholders.
Design data pipelines that meet mission needs using cloud services, orchestration tools, SQL and NoSQL data stores, event streaming platforms, and CI/CD automation.
Assess existing data systems and design integration points, ingestion patterns, and pipeline improvements.
Implement data validation, data quality checks, and automation for data workflows.