AI Data Engineer

4 days ago

Pune, Maharashtra, India Cummins Talent Acquisition Full time ₹ 12,00,000 - ₹ 36,00,000 per year

As a Senior AI Data Engineer at Cummins, you will lead the design, development, and maintenance of scalable data and analytics platforms. You will enable efficient processing, storage, and accessibility of data for analysts, data scientists, and business stakeholders. This role involves working on multiple product teams, collaborating with IT experts and subject-matter specialists, and delivering advanced analytics and AI solutions. You will also mentor junior team members and drive automation and optimization across data engineering processes.

Key Responsibilities:

  • Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and integration solutions for structured, semi-structured, and unstructured data.
  • Build and optimize distributed systems for data ingestion, transformation, and storage from diverse sources (relational, event-based, unstructured).
  • Implement frameworks to monitor, troubleshoot, and ensure data quality and integrity.
  • Design and implement physical data models, indexing, and database structures to optimize performance.
  • Develop and operate large-scale data storage and processing solutions using cloud-based and distributed platforms (Data Lakes, Hadoop, HBase, Cassandra, MongoDB, DynamoDB, etc.).
  • Apply AI/ML concepts to support advanced analytics workflows, including regression, clustering, and time-series analysis.
  • Integrate platforms such as Palantir, Snowflake, and graph databases (Neo4j, TigerGraph) into data pipelines.
  • Establish data governance processes, metadata management, cataloging, and access controls.
  • Automate repetitive data integration and preparation tasks to improve productivity and minimize errors.
  • Collaborate with business and IT stakeholders to understand requirements, plan solutions, and deliver analytics products.
  • Mentor and coach junior team members, promoting best practices in data engineering and analytics.
  • Stay current with AI and data engineering trends, recommending improvements to systems and workflows.

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