At Core Interface, we believe great software is built by small teams of thoughtful engineers working on meaningful problems. Our work supports mission-critical federal programs where the quality and reliability of the data layer directly determines mission outcomes.
We're growing our data engineering team and are looking for ETL-focused engineers across multiple experience levels who take real ownership of the data lifecycle — from ingest through delivery — and communicate clearly about architecture tradeoffs.
What You'll Do in This Role
Design, build, and optimize ETL pipelines for large-scale data ingestion and transformation
Develop custom solutions to ingest, profile, and exploit new and existing data sources
Collaborate with data scientists and analysts to support model development and analytical workflows
Maintain comprehensive data layer documentation for the broader engineering team
Manage all stages of the data lifecycle from ingest planning through display
Collaborate with teammates, service providers, vendors, and mission users to develop more efficient methods
Identify and communicate risks, constraints, and tradeoffs in data architecture decisions
Required Qualifications
Active TS/SCI with Polygraph
U.S. Citizenship
Bachelor's degree in Computer Science, Engineering, or related technical field
Strong Python and/or Java development skills with significant SQL and database experience
Hands-on experience building ETL pipelines in a Linux-based Big Data environment
Experience parsing using Regular Expressions
Experience with interacting with the ELK Stack
Familiarity with RESTful API integration and data source consumption
Clear communication skills in collaborative engineering environments
Additional Strengths That Stand Out
Experience with cloud data platforms (AWS Glue/S3, Azure Data Factory/Synapse, Snowflake, Databricks)
Experience with Apache Spark or similar distributed processing frameworks
Experience with pipeline orchestration tools such as Apache Airflow or equivalent
Experience with Hadoop, HBase, and MapReduce
Prior work in a mission environment or with diverse, complex data types
Containerization experience with Docker and/or Kubernetes
Prior experience supporting AI/ML pipeline development or deployment
Core Interface Benefits
We support our engineers with benefits designed for long-term success:
100% employer-paid medical, dental, and vision (employee + family)
401(k) with 6% company contribution
4 weeks PTO plus 11 federal holidays
Paid parental leave
Government shutdown protection
Tuition assistance and technical training
Internet, phone, and fitness reimbursements
Referral bonuses and spot awards
Quarterly team events
Commitment to Inclusion
Core Interface is an Equal Opportunity / Affirmative Action employer committed to building a workplace where everyone can contribute and grow. All qualified applicants will receive consideration for employment without regard to protected status under applicable law.
Numbers & Facts
Location
Chantilly, Virginia
Skills
Amazon Simple Storage Service (S3)unmatched
Amazon Web Services (AWS)unmatched
Analytical Developmentunmatched
Apacheunmatched
Apache HBaseunmatched
Apache Hadoopunmatched
Apache Sparkunmatched
Application Programming Interface (API)unmatched
Artificial Intelligence (AI)unmatched
Big Dataunmatched
Cloud Computingunmatched
Communication Skillsunmatched
Computer Scienceunmatched
Data Analysisunmatched
Data Scienceunmatched
Database Extract Transform and Load (ETL)unmatched
Dockerunmatched
Documentationunmatched
Fitnessunmatched
Governmentunmatched
Javaunmatched
Linux Operating Systemunmatched
MapReduceunmatched
Microsoft Windows Azureunmatched
Python Programming/Scripting Languageunmatched
REST (Representational State Transfer)unmatched
Regular Expressionsunmatched
Risk Analysisunmatched
SQL Databasesunmatched
Sensitive Compartmented Information (SCI)unmatched
Snowflake Schemaunmatched
Team Lead/Managerunmatched
Team Playerunmatched
Technical Supportunmatched
Top Secret Clearanceunmatched
Tuition Feesunmatched
United States Citizenunmatched
Workflow Analysisunmatched
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