Tactical Data Engineer (TS/SCI)

Responsibilities: : Support continuous data ingest operations, monitoring data feeds, pipeline health, and overall data quality. Visualize and interpret data findings through dynamic reports and dashboards for leadership and users. Use data manipulation and visualization tools to communicate real‑time and historical trends. Collaborate with platform, software, and data engineering teams to reconfigure pipelines for improved reliability. Work with data in multiple formats including Excel, CSV, JSON, and XML. Support incident management processes including issue documentation, resolution, and root‑cause analysis for recurring data outages. Develop and maintain software to automate monitoring of real‑time data feeds, including alerts for timeliness, lineage, volume, and distribution issues. Leverage historical pipeline data to identify improvements in ingest performance and reliability. Assist with designing, developing, testing, and implementing web‑based collaboration and reporting tools. Demonstrate proficiency in Python or Bash scripting for analytics, automation, and data operations. Utilize open‑source analytics and visualization tools to monitor system performance. Qualifications: : Must have an active TS/SCI clearance Bachelor's degree in Computer Science, Mathematics, Engineering, Physics, Information Systems, or related field. 5-15 years of experience in data engineering or related experience At least 1+ years of experience with real-time data streaming Strong experience handling structured and unstructured data across various formats. Proficiency with Python Experience with JSON or XML Experience with any of the following data streaming tools such as: Apache (Kafka, Pulsar, Flink, Storm, Samza, Spark, Beam, Redpanda, or NiFi), Confluent Platform, StreamNative Platform, Cloudera Streaming, AWS Kinesis Data Streams/Firehose, AWS MSK, Google Cloud Data Stream, Google Dataflow (stream mode), RabbitMQ, NATS Jetstream, ZeroMQ. Experience with Linux OS Preferred Experience: Experience with intelligence and C2 data sets (ELINT, COMINT, MASINT, GEOINT). Knowledge of data mining, data modeling, statistics, and machine learning. Exposure or experience with Palantir technologies.