DataOps Engineer

Booz Allen Hamilton•McLean, VA

1d•$62,000 - $141,000•Remote

About The Position

As a DataOps Engineer, your role will be central in enhancing data quality, streamlining data pipelines, and enabling scalable cloud-based solutions that improve the experience for veterans and VA staff. In this role, you will apply modern data engineering practices, automation, and cloud native tooling to solve complex data challenges. Your technical expertise will help guide architecture, build resilient pipelines, and ensure data assets are governed, discoverable, and ready for analytics and application needs across the VA. You will recommend tools and solutions based on your research of current environments, industry standards, and modern DevSecOps and DataOps methodologies. You will partner with software engineers, product teams, architects, and stakeholders to develop and maintain secure, automated, and highly available data services. You will use 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. If you are passionate about repeatability, automation, data reliability, and cloud scale engineering, this is an opportunity to drive meaningful impact in a modernized VA environment. Join us. The world can’t wait.

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

Nice To Haves

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

Responsibilities

Enhancing data quality
Streamlining data pipelines
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
Ensuring data assets are governed, discoverable, and ready for analytics and application needs
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
Designing pipelines using AWS cloud services, orchestration tools, SQL and NoSQL data stores, event streaming platforms, and CI/CD automation to meet mission needs