Data Engineer - Senior 3
SourceoPuneOn-siteDirect career pageEst. 20–35 LPA
Posted on 10 Sept
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Job description
Structured overview of role & requirements
About This Role
- Lead design, development, and maintenance of scalable, efficient, and reliable data pipelines and large-scale data storage solutions supporting analytics, operational reporting, APIs, and AI/ML use cases.
- Implement and enforce data governance, metadata management, and quality controls to enable discoverable, governed, and reusable data assets as part of a Data-as-a-Product model.
- Collaborate cross-functionally with Product Managers, Data Scientists, and business stakeholders to deliver AI-ready datasets and support advanced analytics, GenAI, and intelligent business solutions.
Minimum Requirements
- Bachelor’s degree in Computer Science, IT, Engineering, Data Analytics, or equivalent practical experience required.
- Intermediate experience in data engineering including developing and supporting enterprise data pipelines, data transformations, and data integration using modern cloud platforms and ETL/ELT technologies.
- Technical skills required: SQL, data modeling, performance optimization, scalable data architecture; experience with Spark, Scala/Java, MapReduce, Hive, HBase, Kafka or equivalent is preferred but not mandatory.
- Work Experience Required: Intermediate experience in relevant discipline required; explicit years of experience not stated.
Ideal Candidate Profile
- Experienced working within Agile cross-functional teams involving Product Managers, Data Scientists, and Architects to translate business needs into reusable technical data solutions.
- Familiar with Data-as-a-Product operational models including data cataloging, lineage, metadata, governance, and certification practices.
- Has exposure or familiarity with GenAI, AI/ML data engineering practices, semantic search, vector databases, or AI-ready data preparation supporting enterprise AI solutions.