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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Pantheon Inc - **Location:** Reston, VA, United States (Remote available) - **Experience:** Expert - **Salary:** $140,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Query Performance, Microsoft Word, Microsoft Excel, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Automation of Tests, Batch Processing, Microsoft Outlook, Code Review, Collaborative Software, Databases, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Relational Databases, Database Queries, Document-Oriented Databases, Amazon DynamoDB, Graph Database, Issue Tracking Systems, Python (Programming Language), Machine Learning, Metadata, Microsoft Office, Online Analytical Processing, Online Transaction Processing, Microsoft PowerPoint, Standard Sql, Search Technologies, Microsoft SharePoint, Software Engineering, SQL Databases, Data Streaming, Unstructured Data, Data Logging, Data Ingestion, Delivery Pipeline, Snowflake, Apache Spark, Electronic Medical Records, Indexer, Git, Core Data, Infrastructure Automation Frameworks, Information Technology, AWS Data Analytics, Build Tools, Search Engines, Cloudwatch, Amazon Simple Queue Service (SQS), Software Version Control, Data Pipelines, Docker, Amazon Redshift, Databricks - **Published:** August 29, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/88177738/1 ## About the Role We are seeking a hands-on Data Engineer to help design, build, andoperatethe 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, 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, 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., * Bachelor's degree in Computer Science,Engineering, or a related technical fieldfrom 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 reasonaboutdata 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 communicationskills and the ability to explain data flow, design choices, limitations, and tradeoffs to both technical and non-technical stakeholders. * Ability to work effectively in adistributed, cross-functional engineering environment and produce high-quality work with limitedhand-holding. * Ability to meet deadlines. * 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 withPySpark, 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. ## Description * Design, build, andmaintainreliable 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,participatein 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., * 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, you'll 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. 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