hackajob

Staff Data Engineer - TS/SCI Cleared

Arlington, Virginia · Staff+ · Full-time

No sponsorship$160k-$240kDetected 3 days ago

TypeScriptBigQueryRedshiftAWSKafkaRabbitMQSparkAirflowData EngineeringCybersecurityDNSLeadershipMentoring

About the role

hackajob is collaborating with Twenty to connect them with exceptional professionals for this role.
About The Company America is under sustained cyber attack.
Our adversaries infiltrate our networks, steal our IP, and degrade the digital infrastructure that modern life runs on.

Lead the development and operation of a data lake for cyber operations and intelligence data.
Design schemas, partitions, and indexes that make complex datasets performant and cost-effective to query.
Partner with engineers and intelligence analysts to define query patterns and data products for mission use cases.
Build and evolve ETL pipelines that are observable, recoverable, and resilient to upstream change.
Drive technical initiatives end-to-end, from architecture decisions through production rollout and iteration.
Mentor engineers on data modeling, performance tuning, and production-grade pipeline design.
You collaborate tightly across roles, especially with engineers and analysts who need fast, correct answers.
You will own the data infrastructure that powers Twenty's cyber operations applications and capabilities.
This role is about building a durable, high-performance data lake and the pipelines, schemas, and query patterns that make petabyte-scale datasets usable and economical.
You'll partner closely with engineers and intelligence analysts to turn messy, high-volume operational data into reliable, well-modeled systems that drive real missions.

You have 8+ years of experience in data engineering and/or data architecture.
You have deep experience with data lake architecture and systems used to query data lakes.
You have experience with column-oriented databases in production environments.
You have built data systems from scratch (not only maintained existing platforms).
You have proven leadership experience mentoring engineers and driving technical initiatives.
You are a U.S. citizen and can meet the role's security requirements.

You have experience with key-value datastores.
You have worked with streaming and message queue systems.
You have experience with graph database technologies.
You have worked with internet/networking datasets (e.g., scan data, DNS, netflow, certificates).
You have experience supporting analysts or operational users with high-stakes data needs.
Tech Environment (You Might Work With)
Data lakes: Apache Iceberg, Delta Lake, Apache Hive
Query engines: Trino, Presto, AWS Athena, Apache Spark

Medical, dental, and vision plan options.
Life / AD&D, disability coverage options.
Paid parental leave for eligible full-time employees.
Paid holidays and flexible PTO.
HSA/FSA options, dependent care FSA.
Commuter benefits.
Building fitness center.
Desk setup stipend.
We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability, or any other protected status.
Our vision is American and allied primacy in cyberspace-a future where they cannot contest us, deterrence is assured, and the free world remains secure.
Benefits vary by location, role, and eligibility.

America is under sustained cyber attack.
They've learned-correctly-that those attacks rarely produce consequences.
Twenty was founded to change that, by making our adversaries think twice before they attack us.
Founded in 2024, Twenty Technologies (www.twenty.io) industrializes offensive cyber operations for the U.S. and its allies.
Headquartered in Arlington, Virginia, Twenty has raised $138M from Accel, Caffeinated Capital, Friends & Family Capital, Point72 Ventures, General Catalyst, and In-Q-Tel.
Role Summary

equal opportunity employer.
If you need a reasonable accommodation during the hiring process, let us know and we will work with you.

This listing is sourced directly from hackajob's careers page and normalized into a canonical job model.