Principal Data Engineer

2 days ago

Bangalore, India Autodesk Full time

We are seeking a highly experienced Principal Engineer to lead the design, development, and evolution of our Batch Processing platform , which powers Autodesk’s Analytics Data Platform (ADP). This role requires deep technical expertise in distributed data systems, large-scale pipeline orchestration, and hands-on leadership in shaping next-generation data platform capabilities. You will partner closely with Engineering Managers, Architects, Product teams, and Partner Engineering to modernize our data lakehouse architecture, deliver highly reliable data pipelines, and establish technical excellence across ingestion, processing, and governance. Champion Apache Iceberg-based data lakehouse adoption (versioning, branching, WAP, indexing) Introduce performance optimization patterns for data pipelines (e.g., Establish patterns for metadata-driven, intent-based data processing aligned with AI-assisted pipelines Partner with the Batch Ingestion and Data Security teams to deliver unified ingestion + processing flows Drive modernization initiatives to migrate away from legacy tools Pioneer AI-augmented data engineering practices (e.g., Influence company-wide data engineering strategy by contributing thought leadership and whitepapers 8+ years of experience in software/data engineering, with at least 3 years in big data platform leadership roles ~ Expert in distributed data processing (Spark, PySpark, Ray, Flink) ~ Deep experience with workflow orchestration (Airflow, Dagster, Prefect) ~ Strong hands-on expertise in Lakehouse technologies (Iceberg, Delta, Hudi) and cloud platforms (AWS/Azure/GCP) ~ Proven track record in architecting secure, multi-tenant, and compliant data platforms ~ Skilled in SQL/NoSQL databases, Snowflake, Glue, and modern metadata/catalog tools ~ Experience mentoring engineers, building strong technical culture, and influencing at scale Exposure to AI/ML-driven data engineering (optimizers, anomaly detection, auto-scaling) Experience with data governance, lineage, and observability tools (Atlan, Databand, Collibra, etc.) Familiarity with streaming + batch hybrid architectures (Kappa/Lambda) #

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