Why This Role Stands Out
This role offers an exceptional opportunity to build and scale critical data pipelines on a modern cloud platform, leveraging cutting-edge AI-assisted development tools and a diverse technology stack. You'll thrive here if you're a driven Senior Data Engineer eager to own end-to-end data solutions and tackle complex challenges on an impactful, mission-critical project. Apply today to join a growing company that values innovative engineering and empowers its team to solve hard problems.
Quick Overview
Job Description
If you've ever looked at a fragile data pipeline and thought "I could rebuild this properly," we have one waiting for you. Linchpin Software is growing, and we're looking for a Senior Data Engineer to build and scale the custom data pipeline behind an enterprise visual analytics platform. You'll move high volumes of structured and unstructured data through Kafka, NiFi, Cribl, and Python into Postgres and Splunk, and you'll own it end to end: ingest, parsing, normalization, lineage, and the performance of everything downstream. This is a full-stack data role on a modern cloud platform.
The pipeline runs on AWS and Kubernetes, ships through GitLab CI/CD and Terraform, and feeds analytic UIs that mission users depend on every day. If you want to work across open-source, COTS, and GOTS technologies instead of one vendor stack, this is that job. We build software differently. Our engineers use AI-assisted development tools (Claude Code, Codex, GitLab Duo) every day to design, code, test, and debug faster. You'll spend your time solving hard data problems, not writing boilerplate.
What You'll Do
- Build and optimize secure data ingest pipelines using open-source, COTS, and GOTS technologies
- Engineer ETL in Python with Apache Kafka, Apache NiFi, Cribl, Splunk, and PostgreSQL
- Handle complex data parsing, schema-aligned ingestion, and normalization of diverse structured and unstructured data
- Implement provenance and end-to-end data lineage tracking across the pipeline
- Design and optimize enterprise relational databases and set standards for operations, performance, and security
- Deploy and run the platform on AWS and Kubernetes with Terraform, GitLab CI/CD, and JFrog Artifactory
- Develop data processing workflows and analytics feeding desktop and web-based visual analytic tools
- Integrate new data systems with existing data warehouses and improve performance and functionality
- Mentor junior engineers and contribute to cross-team data standards Required:
- Active Top Secret clearance
- Bachelor's degree
- 8+ years of experience in data engineering, database design, or a related field
- Strong relational database design, SQL, and ETL/ELT skills
- Strong Python skills and experience building production data pipelines
- Experience with streaming and ingest technologies such as Kafka, NiFi, Cribl, or Splunk
- Experience working with structured and semi-structured data and visualization technologies
- Experience improving data workflows, performance, and security
- Ability to work full-time, on-site in Chantilly, VA (20151) Preferred:
- AWS cloud services and Kubernetes in production
- Infrastructure as code and CI/CD (Terraform, GitLab CI/CD, JFrog Artifactory)
- Front-end or full-stack exposure (Vue.js, Flask, Elixir, Phoenix LiveView, Daisy UI)
- High-performance computing and mixed-technology environments
- Federal or secure multi-enclave environments
- Advanced visualization platforms or high-volume data processing
- Data modeling, warehousing, and performance tuning What You'll Gain:
- A pipeline you build and own, across the full stack from ingest to analytic UI
- Broad modern tooling: AWS, Kubernetes, Kafka, NiFi, Terraform, and more
- Daily practice with AI-accelerated engineering, a skill every employer wants
- A small, collaborative team on a stable, long-term mission program
- Competitive compensation and benefits
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