Data Engineer

Amivero•Camp Springs, MD

1d•Onsite

About The Position

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.

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.

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.