Data Engineer (AI-ML Data Systems)

Company Overview

Pantheon Data (a Kenific Holding company) is a private small business based in the Washington DC area. Pantheon Data was founded in 2011 initially providing acquisition and supply chain management services to the US Coast Guard. Our service offerings have grown in the past ten years including infrastructure resiliency contact center operations information technology software engineering program management strategic communications engineering and cybersecurity. We have also grown our customer base to include commercial clients. The company has used this experience to expand our service offerings to other agencies within the Department of Homeland Security (DHS) the Department of Defense (DoD) and other Federal Civilian Agencies.

Position Overview

We are seeking a hands-on Data Engineer to help design build and operate the data foundations that support advanced analytics AI/ML and intelligent document processing solutions. The right candidate is a strong engineer who understands how data moves through real systems: ingestion orchestration transformation quality checks storage query patterns operational monitoring and delivery to downstream applications. This person should be comfortable working across structured semi-structured and unstructured data held in relational graph and vector data stores and should bring the judgment to build pipelines that are reliable explainable maintainable and useful to the engineering teams and products that depend on them.

The ideal candidate has strong Python and SQL skills understands when data should be modeled for operational use versus analytical use and can reason clearly about batch processing event-driven pipelines data quality lineage and downstream consumption. They should be able to become productive quickly in a complex engineering environment ask good questions and build systems that other engineers can trust and extend. Experience with AWS graph databases and query languages such as AQL vector search document data or AI/ML data pipelines is valuable but the core requirement is strong data engineering judgment: knowing how to move structure validate and serve data reliably in support of real products and mission needs.

This role owns the data pipelines and data stores. You will partner closely with the Machine Learning Engineers who own models retrieval extraction and evaluation: they define how documents are chunked embedded enriched and retrieved and you build and run the pipelines and stores that apply those designs reliably at scale.

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.
• Work with graph databases and query languages such as ArangoDB/AQL to model relationships between entities documents and metadata and to support traversal and relationship-driven queries.
• Build and operate vector data pipelines and stores: run embedding generation at scale; manage vector index builds refreshes backfills and re-embedding when models change; and serve the lookups that retrieval and RAG workloads depend on implementing the chunking embedding and metadata specifications defined by the Machine Learning Engineers.
• 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.

Required Skills and Experience

• Bachelors degree in Computer Science Engineering or a related technical field from an 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 search-oriented systems and graph and vector databases.
• 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 work effectively remotely in cross-functional teams.
• Ability to meet deadlines and produce quality work.
• Proficient in Microsoft Suite software including Outlook Word Excel SharePoint and PowerPoint.

Preferred Skills and Experience

• 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.
• Hands-on experience with graph databases and query languages such as ArangoDB/AQL Neo4j/Cypher or Gremlin including graph-shaped data modeling.
• Experience with vector databases or vector search engines such as pgvector OpenSearch or similar including index tuning and hybrid (vector lexical) lookups.
• 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.

Clearance Requirements

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements. Candidates must have the ability to obtain and maintain a Secret clearance; an active Secret clearance is preferred.

Work Location: Reston VA - Remote

• Our company prioritizes the benefits of flexibility and collaboration whether that happens in person or remotely.
• If the position is remote or hybrid you may periodically work from a Pantheon Data office location or client site.
• If this position is assigned to a Pantheon Data office location or client site youll work with colleagues and clients in person as needed for specific client requirements.

Interview Requirement: Candidates who are local to the area should be prepared to participate in an in-person interview as part of the selection process. Candidates outside the local area may be considered for a virtual interview.

Compensation

The salary range for this position is $110000 - $190000. This is not however a guarantee of compensation or salary. Rather salary will be set based on experience geographic location and possibly contractual requirements and could fall outside of this range.

Benefits Overview

We are always looking for good people! Pantheon Data is committed to providing its employees with competitive salaries and benefits in order to increase employee satisfaction and addition to our benefits we also offer SmartBenefits through the Washington Metro Area Transportation Authority where you specify an amount of your pre-tax wages be paid directly to your SmarTrip some cases tuition assistance may be available for continuing education expenses and certifications related to their position. Additional details may be found at Data Important Information

All qualified applicants will be considered for employment without regard to disability status as a protected veteran or any other status protected by applicable federal state local or international law.

As part of the application process you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

If you require reasonable accommodation in completing this application interviewing completing any pre-employment testing or otherwise participating in the employee selection process please direct your inquiries to our Talent Team at or by phone .

This company uses E-Verify to confirm each employees work authorization. For more information click here E-Verify Participation Poster

Required Experience:

IC