Note: The job is a remote job and is open to candidates in USA. Pantheon Data provides engineering, information technology, cybersecurity, and related services to government and commercial clients. The Senior Data Engineer will design, build, and operate reliable data foundations and pipelines supporting analytics, AI/ML, intelligent document processing, and downstream applications. The role involves data ingestion, transformation, modeling, quality validation, orchestration, monitoring, and collaboration with cross-functional engineering teams.
Responsibilities
- Design, build, and maintain reliable data pipelines for structured, semi-structured, and unstructured data sources
- Develop Python-based processing workflows for data ingestion, normalization, validation, enrichment, and transformation
- Work with SQL and relational data stores to support transactional, analytical, and application-facing use cases
- Help design data models and storage patterns appropriate to the workload, including OLTP, OLAP, object storage, document-oriented, search, vector, or graph-oriented patterns when applicable
- Implement orchestration and scheduling for repeatable data workflows using tools such as Airflow, AWS Step Functions, Dagster, Prefect, Glue workflows, or similar technologies
- Build automated quality checks, reconciliation logic, validation reports, and operational alerts so data issues are detected early and can be diagnosed quickly
- Support data pipelines that feed AI/ML, retrieval, document intelligence, analytics, and application workflows
- Collaborate with machine learning engineers, software engineers, cloud engineers, and product stakeholders to turn ambiguous data problems into working software
- Write maintainable code, participate in code reviews, document data flows, and contribute to engineering standards for testing, deployment, observability, and version control
- Help improve the velocity of a growing engineering team by taking ownership of well-scoped data engineering work while continuing to grow into broader system ownership
Skills
- Bachelor's degree in Computer Science, Engineering, or a related technical field from an ABET accredited university
- 5+ years of professional hands-on data engineering, software engineering, analytics engineering, or closely related experience
- Strong Python programming skills, including experience writing maintainable production-oriented code rather than only notebooks or one-off scripts
- Strong SQL skills and practical understanding of data modeling, query performance, joins, indexing, schemas, normalization/denormalization, and data quality
- Understanding of core data engineering concepts, including batch processing, event-driven workflows, ETL/ELT, orchestration, idempotency, retries, backfills, lineage, and failure handling
- Working knowledge of OLTP versus OLAP systems and the tradeoffs between transactional databases, analytical stores, object storage, and search-oriented systems
- Experience building or supporting data pipelines that move data between systems, such as APIs, databases, files, object storage, queues, warehouses, or downstream applications
- Ability to reason about data correctness, schema changes, validation, reconciliation, duplicate handling, missing data, and operational recovery
- Comfortable working with Git, pull requests, code review, issue tracking, documentation, and collaborative software development practices
- Strong communication skills and the ability to explain data flow, design choices, limitations, and tradeoffs to both technical and non-technical stakeholders
- Ability to work effectively in a distributed, cross-functional engineering environment and produce high-quality work with limited hand-holding
- Ability to meet deadlines
- Proficient in Microsoft Suite software including Outlook, Word, Excel, SharePoint, and PowerPoint
- Applicants selected will be subject to a security investigation and may need to meet eligibility requirements. Secret Clearance is required for continued employment
- AWS data services such as S3, Lambda, Glue, Athena, Step Functions, SQS/SNS, Kinesis, EMR, RDS, DynamoDB, Redshift, OpenSearch, or CloudWatch
- Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, AWS Step Functions, Glue, or similar
- Experience with PySpark, Spark, Databricks, EMR, Snowflake, Redshift, or other distributed/analytical data platforms
- Experience supporting AI/ML or RAG-style data workflows, including metadata enrichment, retrieval datasets, vector search, embeddings, evaluation datasets, or human validation workflows
- Experience with document-oriented or unstructured data pipelines, including PDFs, OCR output, tables, forms, images, extracted text, metadata, or search indexes
- Experience with graph databases or graph-shaped data models is a plus
- Experience with Docker, CI/CD, infrastructure as code, automated testing, logging, monitoring, and production support is a plus
- Familiarity with data governance, access control, PII handling, auditability, lineage, and compliance-sensitive environments
Benefits
- SmartBenefits through the Washington Metro Area Transportation Authority, where you specify an amount of your pre-tax wages be paid directly to your SmarTrip account.
- In some cases, tuition assistance may be available for continuing education expenses and certifications related to their position.
- Remote work location in Reston, VA.
- Flexibility and collaboration, whether that happens in person or remotely.
Company Overview