Senior Analytics Engineer (Instrumentation & Data Contracts)

Stefanini Group•Dearborn, MI

19h•Onsite

About The Position

Stefanini Group is hiring! Stefanini is looking for a Senior Analytics Engineer (Data Contracts) in Dearborn, MI (Onsite) For quick apply, please reach out to Fardeen Ali at 248-582-6473/[email protected] We are seeking a skilled candidate to design, build, and maintain efficient data solutions, including infrastructure and pipelines, for processing large volumes of data. The ideal candidate will have expertise in Python, YAML, JSON, and experience in automotive or IoT environments.

Requirements

7+ years of experience in Data Engineering
Expert with GitHub, YAML, and JSON.
Proven ability to write Python Unit Tests for logic validation, mock data, and schema assertions.
Deep understanding of hardware constraints, TCUs, CAN signals, and vehicle states (e.g., Deep Sleep).
Your "customers" are Feature Engineers; aim to simplify their tasks by providing ready-to-use instrumentation assets.
Must have a background in Software Engineering, Data Engineering, or Embedded Systems.
Demonstrated experience using Python, GitHub, and CI/CD pipelines to manage data (not just SQL/Tableau).
Must have prior experience working with hardware-constrained environments (Vehicle Telemetry, Connected Devices, or Embedded Systems) where bandwidth and battery usage are critical factors.
Python, YAML, JSON, SQL, GitHub Actions, CI/CD, PyTest, Automotive (TCU/ECU), IoT Telemetry, Data Contracts

Nice To Haves

5+ Years Total Technical Experience:
3+ Years in "Code-Based" Analytics:
Automotive/IoT Specific:
Telematics

Responsibilities

Translate measurement plans into production-ready Data Contracts (YAML/JSON schemas).
Write reusable Unit Tests (Python/PyTest) for CI/CD pipelines.
Automatically verify event firing and payload accuracy.
Ensure instrumentation respects LTE bandwidth and 12V battery power.
Avoid unnecessary vehicle wake-ups.
Own GitHub versioning.
Ensure updates are backward-compatible to prevent breaking feature builds.
Translate business requests into specific hardware (TCU/ECU) signals and API logic.
Design, build and maintain reliable, efficient and scalable data infrastructure for data collection, storage, transformation, and analysis
Plan, design, build and maintain scalable data solutions including data pipelines, data models, and applications for efficient and reliable data workflow
Design, implement and maintain existing and future data platforms like data warehouses, data lakes, data lakehouse etc. for structured and unstructured data