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Well-known Bangalore startup, mid-level generalist data role with metro location increases candidate competition.
Platform-specific data engineering skills (Hudi, Presto, Airflow) moderately limit cross-industry transferability.
Explicit 4–6 years and mandatory Hudi/Presto/Airflow skills create high filtering rigidity.
Design, build, and operate scalable batch and near-real-time data pipelines powering product, business, growth, and ML use cases.
Develop and improve lakehouse architecture using Apache Hudi; maintain query engines like Presto/Trino and workflow orchestration with Apache Airflow.
Ensure data platform reliability, quality, performance, cost optimization; create reusable data models and reliable data marts for analytics and product teams.
4-6 years of data engineering experience, preferably at scale.
Hands-on experience with Apache Airflow or similar orchestration systems.
Strong knowledge of Presto/Trino or other distributed query engines.
Experience with Apache Hudi concepts including copy-on-write vs merge-on-read, upserts, incremental reads, compaction, partitioning, and schema evolution.
Strong background in distributed data processing and storage system design with ability to build reliable ETL/ELT pipelines.
Proficient in SQL and at least one programming language such as Python, Java, or Scala with strong debugging and production ownership skills.
Experienced in designing and improving complex data architectures (Data warehouse, Lakehouse, Lambda/Kappa, Medallion, Event-driven) and partnering with cross-functional teams to deliver scalable data platform solutions.