DataOps Engineer

Booz Allen Hamilton is focused on enhancing data quality and streamlining data pipelines to improve the experience for veterans and VA staff. As a DataOps Engineer, you will apply modern data engineering practices and automation to solve complex data challenges, guiding architecture and building resilient data pipelines.

Responsibilities:

• Enhancing data quality, streamlining data pipelines, and enabling scalable cloud-based solutions
• Applying modern data engineering practices, automation, and cloud native tooling to solve complex data challenges
• Guiding architecture, building resilient pipelines, and ensuring data assets are governed, discoverable, and ready for analytics and application needs across the VA
• Recommending tools and solutions based on research of current environments, industry standards, and modern DevSecOps and DataOps methodologies
• Partnering with software engineers, product teams, architects, and stakeholders to develop and maintain secure, automated, and highly available data services
• Using technologies including AWS cloud services, orchestration tools, SQL and NoSQL data stores, event streaming platforms, and CI/CD automation to design pipelines that meet mission needs

Requirements:

• 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 SQL and a scripting or programming language such as Python, Bash, or Java
• Experience working 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
• Public Trust
• HS diploma or GED
• Experience with AWS cloud services such as S3, Glue, Lambda, RDS, Redshift, EMR, Kinesis, or Step Functions
• Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, or AWS Managed Workflows
• Experience with Azure cloud services such as Azure Blob Storage, Azure Data Factory, Azure Functions, Azure SQL Database, Azure Synapse Analytics, formerly SQL Data Warehouse, 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 related field
• Cloud practitioner, data engineer, or architect certification