Senior/Lead Data Engineer
The project is in the Explore (Discovery) phase of ATLAS (VLAOps), a Greenfield initiative to build a foundational Visual-Language-Action ecosystem for autonomous heavy machinery in mining and construction. The goal is to design a data architecture that bridges existing machine health telemetry with a new digital operator data layer. During this 8-week phase, the Data Engineer will develop a data architecture blueprint, conduct a data readiness audit, and define an ingestion strategy to transfer large volumes of unstructured edge data into the Helios Data Lake using a Medallion (Bronze/Silver/Gold) architecture.
Essential functions
- Ingestion Strategy: Design pipelines to move data from the "raw edge" (wired/physical transfer) to a managed cloud environment.
- Data Readiness Audit: Analyze existing "Unstructured Operator Data" inventories to determine quality and availability for training.
- Architecture Design: Define the Medallion Infrastructure (Bronze/Silver/Gold) specifically for VLA data, separating it from legacy Machine Health data.
- ETL/ELT Design: Blueprint the logic for filtration, correction, and aggregation required before training can begin.
Qualifications
• Strong Python is mandatory (for parsing binary files/logs).
• Experience with Big Data Frameworks: Spark, Databricks.
• Experience handling Unstructured Data (ROS bags, Video, Images, LiDAR, Log files).
• Architecture: Cloud Data Lakes (AWS/Azure), Medallion Architecture (Raw → Curated → Enriched), and ETL/ELT pipeline design.
• Knowledge of Edge computing constraints (handling 2-5GB/min data generation that cannot be streamed live)
Would be a plus
• Familiarity with Robotics or Autonomous Vehicle data structures (specifically ROS/bag files).
• Experience with Industrial IoT (IIoT) telemetry or high-frequency sensor data.
• Experience designing architectures that strictly separate experimental data (Behavioral) from production data (Machine Health) to prevent "polluting" the main data lake.
• Ability to perform "Gap Analysis" on scattered data inventories rather than just executing defined tickets
We offer
- Work on bleeding-edge projects on a team of experienced engineers
- Flexible working hours
- Specialization courses
- 24 days annual leave + an additional of 5 sick days
- Floating Holidays
- Private medical subscription for employees
- Benefits basket with the total value of 650 euro net/year
About us
Grid Dynamics (NASDAQ: GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience. Founded in 2006, Grid Dynamics is headquartered in Silicon Valley with offices across the Americas, Europe, and India.