Technical Lead – Data Engineering
Myntra (company site, opens in a new tab)6+ yrsBengaluruOn-siteDirect career pageEst. 30–48 LPA
Posted 10h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, build, optimize, and operate large-scale batch data processing systems, ETL pipelines, and workflow orchestration platforms using Spark, Airflow/Dagster, dbt, and Databricks.
- Lead end-to-end ownership of production data pipelines including architecture, performance optimization, troubleshooting, and operational reliability at Myntra scale.
- Develop AI-native data engineering capabilities that automate SQL/pipeline generation, optimization, code reviews, and embed intelligent data quality, governance, and human-in-the-loop safeguards.
Minimum Requirements
- 6+ years of hands-on experience in Data Engineering or Software Engineering with production data systems at scale.
- Deep expertise in Apache Spark/PySpark, Spark SQL, programming in Python/Java/Scala; strong advanced SQL and query optimization skills.
- Experience building and operating production-grade ETL/ELT pipelines, using workflow orchestration tools like Apache Airflow or Dagster, and Databricks or equivalent platforms.
- Strong data modeling, lakehouse architecture knowledge, and experience with data quality, metadata, lineage, and governance standards.
Ideal Candidate Profile
- Senior individual contributor comfortable with technical ownership of complex large-scale production data systems from design to operations and root-cause analysis.
- Expertise spanning Spark internals, SQL, Python, orchestration DAGs, data modeling, lakehouse technologies, and platform architecture.
- Experienced in driving technical leadership through architecture/design reviews, mentoring, and building reusable frameworks; enthusiastic about integrating AI/ML to enhance data engineering workflows.