Data Engineer (Streaming & Sensor Data)

Addx Corporation; Colorado Springs (CO); On-site; USD 90,000 - 130,000; Full time

Job summary

Addx Corporation is seeking a Data Engineer to build the data foundation for ML apps in Colorado Springs (and Denver considered). You will integrate time-series measurements from radar and OPIR data, real-time streams, databases, and systems with varying extraction capabilities, using Python and AWS.

You will collaborate with the ML team to characterize data, establish reliable pipelines, deliver cleaned datasets, and shape the architecture for scalable, traceable data processing.

Qualifications

• Experience designing, implementing, and operating production streaming and batch data pipelines and their supporting storage systems.
• Strong software engineering skills, including maintainable code, automated testing, version control, and deployment.
• Practical understanding of streaming behavior, including filtering, consumer progress, buffering, failure recovery, and replay.
• Experience organizing time-series, telemetry, sensor, or similarly complex data, with an understanding of schema evolution, partitioning, and efficient access patterns.

Responsibilities

• Understand our data sources. Investigate interfaces, formats, coverage, data volumes, and quality. Document findings to guide implementation and capacity planning.
• Build ingestion pipelines. Develop workflows for streaming and historical data across databases, APIs, files, and interfaces. Implement configurable filtering for downstream messages.
• Shape the data architecture. Evaluate processing, storage, and access options against workloads, reliability, and cost; document decisions.
• Deliver trusted datasets. Establish consistent schemas, timestamps, units, identifiers, and source metadata; implement validation and access methods for ML workflows.
• Operate reliable systems. Build tested pipelines with deployment, monitoring, and access controls; handle out-of-order data and recovery procedures.

Skills

Streaming data pipelines

Software engineering

Time-series data

Job description

We’re hiring people who love our great nation—engineers, analysts, and operators who want their work to directly contribute to the strength of U.S. national security. Bring your skills, curiosity, and integrity; we’ll back you with modern tools, mentors, and clear paths for growth.

Location: Colorado Springs, CO

Job Id:1065

# of Openings:1

Location: Primarily Colorado Springs, CO; Denver, CO, also considered

We are seeking a Data Engineer to build the data foundation for our machine learning applications. You will integrate time-series measurements, including radar and OPIR data, from real-time streams, application databases, and systems with varying extraction capabilities. You will collaborate with senior technical staff and the ML team to characterize available data, establish reliable pipelines, and deliver cleaned, standardized datasets. You will help select technologies and develop an architecture based on measured workloads, application needs, and operational requirements. Our development environment is primarily Python, with AWS as the preferred cloud platform.

In this role, you will:

• Understand our data sources. Investigate available interfaces, message formats, historical coverage, data volumes, arrival rates, and quality limitations. Document findings to guide implementation and capacity planning.
• Build ingestion pipelines. Develop maintainable workflows for streaming and historical data across databases, APIs, files, and application-specific interfaces. Implement configurable filtering to capture the messages and measurements needed downstream.
• Shape the data architecture. Evaluate processing, storage, and access options against representative workloads, reliability needs, interoperability, operational complexity, and cost. Document decisions and support the architecture’s evolution as requirements become clearer.
• Deliver trusted datasets. Establish consistent schemas, timestamps, units, identifiers, and source metadata while preserving measurement meaning. Implement validation and traceability, and define dependable access methods with the ML team. Support future feature, labeling, and training-data workflows.
• Operate reliable systems. Build tested, documented pipelines with repeatable deployment, monitoring, and appropriate access controls. Handle duplicate, missing, delayed, and out-of-order data, and implement recovery and reprocessing procedures.

We’re looking for someone with:

• Experience designing, implementing, and operating production streaming and batch data pipelines and their supporting storage systems.
• Strong software engineering skills, including maintainable code, automated testing, version control, and deployment.
• Practical understanding of streaming behavior, including filtering, consumer progress, buffering, failure recovery, and replay.
• Experience organizing time-series, telemetry, sensor, or similarly complex data, with an understanding of schema evolution, partitioning, and efficient access patterns.

Demonstrated ability to investigate unfamiliar systems, evaluate technical tradeoffs, and communicate recommendations while balancing reliability, performance, maintainability, and cost.

Additional experience that would be valuable:

• Python-based data processing and AWS or comparable cloud infrastructure.
• Radar, OPIR, or other sensor measurement data.
• Workflow orchestration, containers, infrastructure as code, and automated delivery.
• Dataset versioning, feature generation, labeling, or training-data preparation.