Data Platform Engineer for Real-Time Ingest & Analytics

MatrixSpace; Burlington (MA); On-site; USD 110,000 - 160,000; Full time

Job summary

MatrixSpace is seeking a hands-on Data Engineer to design, build, and optimize the data infrastructure powering our radar sensing platform. You will create scalable pipelines ingesting data from field deployments and organize it to accelerate AI improvements across teams.

The role emphasizes reliability, observability, and performance, with opportunities to influence technology choices, work across analytics, product, and infrastructure, and support long-term product growth.

Qualifications

• 4–6 years of experience in Data/Backend/DB roles.
• Strong programming experience in Python, C++, Golang, or similar languages.
• Experience building and operating real-time and batch data pipelines in production environments.
• Deep expertise with PostgreSQL, including performance tuning, indexing, partitioning, and schema design.

Responsibilities

• Design the internal data platform enabling ingestion, organization, and analysis of data from deployed radar systems.
• Build data ingestion, transformation, enrichment, aggregation, and publishing workflows.
• Develop solutions across relational, NoSQL, in-memory, time-series, warehouse, and data lake technologies.
• Optimize PostgreSQL databases through schema design, indexing, partitioning, and query tuning.
• Implement advanced analytics, aggregation, and statistical processing across large datasets.
• Monitor pipeline reliability, performance, data quality, and system observability.

Skills

Python

C++

Golang

Data pipelines

PostgreSQL

NoSQL

Communication

Tools

PostgreSQL

NoSQL

Airflow

Parquet

Delta Lake

Kafka

Job description

MatrixSpace is seeking a hands-on Data Engineer to design, build, and optimize the data infrastructure powering our radar sensing platform. You will create scalable pipelines ingesting data from field deployments and organize it to accelerate AI improvements across teams.

The role emphasizes reliability, observability, and performance, with opportunities to influence technology choices, work across analytics, product, and infrastructure, and support long-term product growth.