Senior Data Engineer (python, Ai)

Autodesk Autodesk · Enterprise · Bangalore, India

Senior Data Engineer role focused on building and maintaining data engineering pipelines, data quality, reliability, and observability standards using modern data technologies and cloud platforms. The role involves modernizing legacy workflows, developing ETL/ELT processes, and enabling analytics. Familiarity with AI/ML techniques for data engineering and AI-assisted development tools is mentioned.

What you'd actually do

  1. You will need a product-focused mindset. It is essential for you to understand business requirements and architect systems that scale and extend to accommodate those needs
  2. Break down complex problems, define technical solutions, and sequence of work to enable fast, iterative improvements
  3. Design, build, and maintain scalable data pipelines and data models across Access
  4. Modernize legacy data workflows and infrastructure, including migrations from platforms such as Hive to Iceberg
  5. Develop reliable ETL/ELT workflows to ingest, transform, and serve data for analytics and operational use cases

Skills

Required

  • 6–8 years of experience in data engineering or related roles
  • Strong proficiency in SQL
  • Strong proficiency in programming languages such as Python
  • Experience building data pipelines using modern data technologies (e.g., Spark, Airflow, Snowflake, or similar)
  • Experience with cloud-based data architectures (AWS, Azure, or GCP)
  • Experience building dashboards and analytics in Looker and/or Power BI
  • Experience with version control and CI/CD tools like Git and Jenkins CI
  • Experience with streaming architectures and Flink-based processing
  • Strong understanding of data modeling
  • Strong understanding of pipeline reliability
  • Strong understanding of large-scale data processing
  • Experience working with notebook solutions like Jupyter, EMR Notebooks, or Apache Zeppelin
  • Experience leveraging AI-assisted development tools (e.g., GitHub Copilot, Cursor, Claude Code) to improve development productivity and code quality
  • Familiarity with applying AI/ML techniques to data engineering workflows, including data transformation, anomaly detection, or pipeline optimization
  • Bachelor's degree in Computer science, Engineering, or related field, or equivalent practical experience

Nice to have

  • Experience with data platform modernization or large-scale data migrations
  • Experience working with identity, access, compliance, or entitlement-related datasets
  • Familiarity with Model Context Protocol (MCP) servers or similar frameworks for enabling AI-agent interactions with data systems

What the JD emphasized

  • product-focused mindset
  • understand business requirements
  • architect systems that scale
  • solve hard problems around reliability, resiliency, and scalability
  • Modernize legacy data workflows and infrastructure
  • reliable ETL/ELT workflows
  • applying AI/ML techniques to data engineering workflows