Data Engineer (6458)

As Data Engineer, you’ll design and maintain scalable data pipelines and cloud-based data platforms that support advanced analytics and machine learning workloads. You will also leverage Python, distributed data processing frameworks, and AWS services to ingest, transform, and manage structured and unstructured data across a variety of sources. The ideal candidate will collaborates with engineers and stakeholders to build reliable data architectures, ensuring efficient data access, integration, and performance in production environments.

We know that you can’t have great technology services without amazing people. At MetroStar, we are obsessed with our people and have led a two-decade legacy of building the best and brightest teams. Because we know our future relies on our deep understanding and relentless focus on our people, we live by our mission: A passion for our people. Value for our customers.

If you think you can see yourself delivering our mission and pursuing our goals with us, then check out the job description below!

What you’ll do:

• Design and implement data ingestion, transformation, and enrichment pipelines across multiple concurrent projects with varying data modalities (time-series sensor data, video, images, documents, and metadata).
• Develop and manage cloud-native data services including object storage workflows, vector database integration, and structured data warehousing to support multi-modal AI/ML systems.
• Work closely with AI/ML engineers to operationalize data pipelines that feed training, inference, and retrieval-augmented generation (RAG) workloads in production.
• Establish data quality, lineage, and governance practices across projects that are maturing from prototype to product, bringing structure and repeatability to evolving data ecosystems.
• Support the processing and organization of unstructured data (video files, PDFs, technical manuals) into formats suitable for embedding generation, semantic search, and summarization.
• Present technical approaches and data architecture decisions to both technical teammates and non-technical stakeholders.

What you’ll need to succeed:

• Bachelor's Degree in Computer Science, Data Science, Information Systems, Engineering, or a comparable technical discipline.
• An active Secret clearance or the ability to obtain
• 2-4+ years of professional experience in data engineering, data platform development, or a closely related technical role.
• Relevant cloud or data engineering certifications are a plus (e.g., AWS Certified Data Engineer, Databricks Data Engineer Associate, AWS Solutions Architect, or equivalent)
• Strong proficiency in Python for data engineering (scripting, pipeline development, data transformation).
• Experience designing and building ETL/ELT pipelines for structured and semi-structured data in cloud environments.
• Experience with AWS cloud services for data workflows (S3, RDS, DynamoDB, EC2/ECS, and related services).
• Hands-on experience with at least one distributed data processing framework (Databricks, Spark, Dask, Ray, or equivalent).
• Demonstrated ability to work with diverse data modalities (time-series, sensor telemetry, image, video, unstructured text).
• Experience with SQL and data warehousing concepts (schema design, partitioning, incremental processing).
• Strong experience with data pipeline orchestration, scheduling, and monitoring in production environments.
• Experience building data pipelines that ingest, transform, or serve data through RESTful APIs.
• Strong communication skills with the ability to explain data architecture decisions to both ML engineers and non-technical stakeholders.

This role is hybrid, with a requirement to be in our Reston HQ office a minimum of 3 days/week.

SALARY RANGE: $119,000 - 129,000

The salary range for this position is determined based on qualifications, skills, and relevant experience. The final salary offered will be determined based on several factors including:

• The candidate's professional background and relevant work experience
• The specific responsibilities of the role and organizational needs
• Internal equity and alignment with current team compensation
• This role is also eligible for additional compensation, subject to the terms and policies of MetroStar, which may include:
• Performance-based bonuses
• Company-paid training and/or certifications
• Referral bonuses