Data Engineer Jobs

About The Position

Requirements

• Active Secret security clearance
• Bachelor’s degree in information technology , c omputer s cience, e ngineering, or related technical discipline. ( Equivalent experience may be considered. )
• Minimum five (5 ) years of experience with a combination of: Modern data engineering platforms (Azure Data Factory, AWS Glue, Databricks, Kafka, Spark, Flink, etc.).
• Strong skills in building data ingestion and streaming pipelines.
• Proficiency in Python, SQL, or similar languages.
• Knowledge of data modeling, ETL/ELT patterns, and distributed systems.
• Familiarity with telemetry sources (logs, metrics, events) and common security/monitoring tools.
• Experience with cloud storage systems (S3, ADLS, GCS) and data warehouses/lakehouses.
• Understanding of data governance, lineage, and quality frameworks.
• Good technical communication skills
• Proficiency with Microsoft Office Suite, including Word, Power-Point, Excel, Project, and Outlook.
• Ability to travel approximately 25% to support customer locations, mission partner engagements, and operational activities.

Nice To Haves

• Experience with observability stacks (Elastic, Splunk, Azure Monitor, Grafana, OpenTelemetry).
• Exposure to analytics platforms or ML integration.
• Infrastructure‑as‑code experience (Terraform, ARM/Bicep).
• Experience with Zero Trust or security‑centric telemetry.

Responsibilities

• Design and implement scalable telemetry ingestion pipelines across cloud, endpoint, network, and application sources.
• Build real‑time and batch processing work-flows using modern data engineering tools and technologies.
• Develop data models, schemas, and metadata structures to support analytics, dashboards, and machine learning.
• Optimize pipeline performance, reliability, observability, and data quality.
• Integrate telemetry from identity systems, logging platforms, monitoring tools, and security technologies.
• Create automation for ETL/ELT processes, data normalization, and event enrichment.
• Collaborate with analytics, cloud, security, and platform engineering teams to define data requirements.
• Ensure pipeline governance, compliance, retention, and secure data handling.
• Troubleshoot ingestion issues, latency problems, schema drift, and data integrity concerns.
• Document pipeline architecture, data flow diagrams, and operational procedures.