Role Overview
Ford Motor Company offers an engineering opportunity for a Senior Data Engineer within the Pro 360 Data Analytics & AI Portfolio under Enterprise Technology in Chennai, Tamil Nadu, India (Hybrid). In this technical role supporting the Ford Pro Commercial business, you will design, build, and optimize scalable ELT/ETL pipelines and core data infrastructure. The position focuses on migrating and integrating multi-tier data structures from on-premise platforms (Hadoop, SQL Server) into Google Cloud Platform (BigQuery), engineering cloud-native data services, and partnering with Data Science and Business Intelligence teams across Global Data Insight & Analytics (GDI&A) to deliver high-quality data layers.
Core Responsibilities
- Data Pipeline Development: Architect and operationalize distributed batch and streaming ELT/ETL pipelines to ingest data into Google BigQuery from diverse source systems.
- Platform Migration & Hybrid Data Integration: Interface with on-premise legacy systems (Hadoop, SQL Server) and construct automated extraction flows using GCP data tools and Informatica to modernize data repositories.
- Cloud-Native Services & APIs: Design, build, and deploy cloud-native microservices and RESTful data APIs to expose analytics datasets to partner developers and enterprise applications.
- Data Pipeline Optimization & Monitoring: Monitor runtime telemetry, diagnose bottlenecks, and tune distributed query and pipeline performance for fault tolerance and cost efficiency.
- Data Science Collaboration: Deliver optimized, governed feature sets and analytic tables to data scientists, enabling reliable advanced machine learning model training and operationalization.
- Technical Governance: Provide technical guidance on schema design, data transformation models, and data quality validation across business domains.
Qualifications & Requirements
- Educational Background: Bachelor's degree in Computer Science, Data Science, Information Technology, or an equivalent engineering discipline (M.S. in a quantitative or science-based discipline preferred).
- Core Technical Experience: 3+ years of dedicated hands-on programming with SQL and Python, coupled with proven experience building distributed, fault-tolerant data pipelines from scratch.
- Cloud Platform Proficiency: 2+ years of experience with Google Cloud Platform (GCP) or Amazon Web Services (AWS) data services; candidates with 5+ years building enterprise ETL pipelines using Informatica and traditional data warehouses will also be considered.
- Database Systems: Deep practical familiarity with both relational and NoSQL database engines, including schema modeling and performance tuning.
- Preferred Big Data Ecosystem: Direct hands-on experience with native GCP services (BigQuery, Cloud Composer, Dataflow, Cloud SQL, GCS, Cloud Functions, Pub/Sub) or open-source distributed frameworks (Apache Spark, Kafka, Hive, Scala).
About Ford Motor Company
Ford Motor Company is a global automotive and mobility technology enterprise dedicated to advancing connected, electric, and commercial software solutions, driving operational excellence and customer value across international markets.