Data Engineer

The Gist

The Data Engineer is responsible for designing, developing, implementing, and maintaining enterprise data pipelines, data integration solutions, and scalable data architectures that support analytics, reporting, machine learning, and operational systems. The individual ensures the availability, quality, reliability, and performance of data assets across cloud and hybrid environments.

Special Requirements

• US Citizenship required to obtain Public Trust
• Must be local to the DMV area
• Bachelor's Degree

Responsibilities

• Design, develop, and maintain enterprise data pipelines supporting data ingestion, transformation, integration, and analytics workloads
• Build and optimize data architectures that support reporting, analytics, operational systems, and machine learning initiatives
• Develop ETL and ELT processes to support enterprise data management and integration requirements
• Implement data quality controls, validation processes, and governance standards to ensure data integrity and reliability
• Support real-time and batch data processing solutions across cloud-based and hybrid environments
• Collaborate with Data Scientists, Business Analysts, architects, and application development teams to support data-driven initiatives
• Monitor and optimize data platform performance, scalability, reliability, and operational efficiency
• Support data migration, modernization, and cloud transformation initiatives
• Implement security controls and compliance requirements for enterprise data environments
• Develop and maintain technical documentation, data dictionaries, architecture diagrams, and operational procedures

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical discipline
• Experience designing, building, and maintaining scalable enterprise data pipelines and data architectures
• Experience utilizing Python, SQL, Spark/Scala, Databricks, and distributed data processing technologies
• Experience supporting AWS cloud environments utilizing S3, Kinesis, Lambda, Aurora, RDS, OpenSearch, CloudFormation, and CloudWatch
• Experience working with relational and non-relational databases including PostgreSQL, Oracle, SQL Server, Redis, Aurora, and OpenSearch
• Experience implementing ETL and ELT solutions, data integration frameworks, and enterprise data management practices
• Experience supporting real-time data streaming and event-driven architectures utilizing Kafka and Confluent Kafka
• Experience utilizing GitHub Enterprise, Harness, CI/CD pipelines, Terraform, Docker, and Kubernetes to support modern data engineering practices
• Experience implementing data quality controls, data governance standards, and operational monitoring solutions
• Strong analytical, troubleshooting, and problem-solving skills with the ability to support complex enterprise data environments

Qualifications

Commensurate with experience

Skills

• Python
• SQL
• Spark/Scala
• Databricks
• Distributed data processing technologies
• AWS cloud environments
• S3, Kinesis, Lambda, Aurora, RDS, OpenSearch, CloudFormation, and CloudWatch
• Relational and non-relational databases
• ETL and ELT solutions
• Data integration frameworks
• Enterprise data management practices
• Real-time data streaming and event-driven architectures
• GitHub Enterprise, Harness, CI/CD pipelines, Terraform, Docker, and Kubernetes
• Data quality controls
• Data governance standards
• Operational monitoring solutions

Benefits

• Workforce development initiatives
• Stipend for ongoing tech training
• Flexible work schedule
• Retirement support
• Incentives for meeting performance targets
• Family events
• Volunteer opportunities
• Referral rewards

Pay

TBD

Schedule

TBD

Benefits

• Workforce development initiatives
• Stipend for ongoing tech training
• Flexible work schedule
• Retirement support
• Incentives for meeting performance targets
• Family events
• Volunteer opportunities
• Referral rewards