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TwentyTwentyArlington, VA

Staff Data Engineer - TS/SCI Cleared

Leads development of high-performance data lakes and ETL pipelines for petabyte-scale cyber operations data. Partners with engineers and analysts to build reliable data systems, drives technical initiatives, and mentors team members. Requires 8+ years experience and TS/SCI clearance.

Salary not listed
On-site8+ YOEData Engineering

About the role

Responsibilities

  • 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.
  • Establish best practices for data quality, documentation, and operational ownership across the platform.
  • Mentor engineers on data modeling, performance tuning, and production-grade pipeline design.
  • Identify bottlenecks in storage/compute/query layers and ship improvements with clear performance wins.

Requirements

  • 8+ years of experience in data engineering and/or data architecture.
  • Mastery-level expertise building ETL pipelines and operating them in production.
  • Deep experience with data lake architecture and systems used to query data lakes.
  • Strong schema and index design skills, including partitioning, indexing, and clustering strategies.
  • Experience with column-oriented databases in production environments.
  • Built data systems from scratch (not only maintained existing platforms).
  • Proven leadership experience mentoring engineers and driving technical initiatives.
  • U.S. citizen with active TS/SCI security clearance with appropriate polygraph.

Nice To Haves

  • Experience with key-value datastores.
  • Worked with streaming and message queue systems.
  • Experience with graph database technologies.
  • Worked with internet/networking datasets (e.g., scan data, DNS, netflow, certificates).
  • Experience supporting analysts or operational users with high-stakes data needs.

Tech Stack

Data lakes: Apache Iceberg, Delta Lake, Apache Hive
Query engines: Trino, Presto, AWS Athena, Apache Spark
Column stores: ClickHouse, Amazon Redshift, Google BigQuery
ETL / orchestration: Airflow, AWS Glue, NiFi, ClickPipe
Streaming / queues: Kafka, RabbitMQ, NATS, AWS Kinesis
Graph: Neo4j, AWS Neptune, Memgraph, Apache AGE

Skills

Apache IcebergDelta LakeApache HiveTrinoPrestoAws AthenaSparkClickHouseAmazon RedshiftGoogle BigqueryAirflowAws GlueApache NifiKafkaEtl Pipelines

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