Senior Data Platform Architect

Grid Dynamics is building a senior architecture team for a cutting-edge construction autonomy (physical AI) program at a global heavy-equipment manufacturer. The program focuses on autonomous machines capable of operating unsupervised at customer sites. It connects on-machine sensor data collection, cloud-based data curation and annotation, end-to-end vision-language-action (VLA) model training, and simulation.

As a Senior Data Platform Architect, you will shape the data architecture that transforms raw sensor data into trusted, reusable datasets for ML training and simulation. The data includes camera images, LiDAR and radar point clouds, GNSS/IMU signals, and machine telemetry. You will work closely with the US-based Data Platform Architect Lead and collaborate with teams responsible for perception, sensor kits, robotics, and autonomy. The platform is largely greenfield, and the role combines architectural ownership with hands-on delivery.

This is an opportunity to contribute to a large-scale physical AI program, helping establish the data foundations for autonomous machines.

Responsibilities

• Design data curation and annotation workflows from raw data ingestion to training dataset creation.
• Define metadata registries and cataloging approaches for sensor assets, including machine and sensor identifiers, calibration versions, timestamps, pose, and data storage layers.
• Establish data lineage, versioning, lifecycle management, and retention from raw sensor logs to training datasets.
• Define how real-world data is prepared for simulation and how synthetic data is stored, versioned, and combined with real data.
• Agree on data contracts with perception and sensor-kit teams.
• Collaborate with the US-based Data Platform Architect Lead on the end-to-end data architecture.
• Produce actionable architecture artifacts that engineering teams can implement.
• Work hands-on to turn architectural decisions into working software quickly, using AI coding tools.

Requirements

• Background in data architecture or engineering for large-scale platforms, with hands-on delivery.
• Strong knowledge of unstructured and binary data, including images, video, and point clouds stored in object storage.
• Hands-on expertise in metadata catalogs, registries, and asset management.
• Solid understanding of ML data preparation, including curation, dataset splits, holdouts, and reproducible dataset versions.
• Practical knowledge of data lineage and versioning from raw data to training datasets, using LakeFS, DVC, Delta, or equivalent tools.
• Familiarity with lakehouse formats such as Parquet, Iceberg, or Delta.
• Proficiency in batch and streaming ingestion using technologies such as Kafka or Kinesis.
• Hands-on skills with at least one major cloud platform (AWS, Azure, or GCP) and data processing engines such as Spark or Databricks.
• Proficiency in Python.
• Ability to use AI coding tools to accelerate hands-on development and delivery.

Nice to have

• Background in autonomous vehicle, robotics, or ADAS data pipelines.
• Familiarity with ROS bags, MCAP, sensor logs, drive data, or scene data.
• Knowledge of annotation and labeling pipelines, including auto-labeling.
• Exposure to synthetic or simulated imagery and sensor data for training or testing.
• Familiarity with ML experiment and artifact tracking tools such as MLflow.

We offer

• Opportunity to work on bleeding-edge projects
• Work with a highly motivated and dedicated team
• Competitive salary
• Flexible schedule
• Benefits package - medical insurance, sports
• Corporate social events
• Professional development opportunities
• Well-equipped office

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.