Meesho
About this role
Meesho is one of India's largest ecommerce platforms, and the posting says 5 percent of Indian households shop there. This is a data platform seat on systems that carry that volume: the company describes serving microservices at 15,000 requests per second on normal days and 30,000 during sales, with SLAs around 10 milliseconds, and a distributed scheduler tracking more than 50 million shipments. The role is distributed data systems work in Java, Scala or Python with heavy SQL. What lifts it above a standard data engineering job is the depth asked for: Spark internals including Catalyst, Tungsten and shuffle, with experience customising or contributing to open source. The stack spans Kafka, Spark, Hive, Delta Lake, Presto or Trino, Airflow and lineage tools. Apply if you have tuned Spark at terabyte scale and want Indian consumer internet volume.
Who this is for
Requirements as published:
- 5 to 8 years of professional experience in software or data engineering, focused on distributed data systems.
- Strong programming in Java, Scala or Python, and expertise in SQL.
- At least 2 years hands on with big data systems including Apache Kafka, Apache Spark, EMR or Dataproc, Hive, Delta Lake, Presto or Trino, Airflow, and data lineage tools such as DataHub, Marquez or OpenLineage.
- Experience implementing and tuning Spark, Delta Lake and Presto at terabyte scale or beyond.
- Strong understanding of Apache Spark internals (Catalyst, Tungsten, shuffle) with experience customising or contributing to open source code.
- Familiarity with a modern open source and cloud native data stack: Apache Iceberg, Hudi or Delta Lake; Trino, Presto, DuckDB, ClickHouse, Pinot or Druid; Airflow, Dagster or Prefect; dbt, Great Expectations, DataHub or OpenMetadata; Kubernetes, Terraform and Docker.
- Strong analytical and debugging skills for complex issues in large scale systems.
The actual day to day:
- Building and running data infrastructure for a platform handling millions of orders daily.
- Working inside a pod aligned to a business theme, contributing to solution design rather than only implementation.
- The posting says engineers are expected to challenge existing solutions, not just build to spec.
Location and office reality:
- Bangalore. Office days are not stated in the posting.
Honest fit guidance:
- The Spark internals requirement is the real filter. Many candidates have used Spark; far fewer can talk about Catalyst and shuffle behaviour credibly.
- Meesho describes a culture that values speed over perfection and logical debate over authority. That suits some people and not others, and it is worth taking literally.
- The scale numbers in the posting are unusually concrete for an Indian ecommerce role, which makes this a good one for a CV if you want volume experience.
- 5 to 8 years of professional experience in software or data engineering, focused on distributed data systems.
- Strong programming in Java, Scala or Python, and expertise in SQL.
- At least 2 years hands on with big data systems including Apache Kafka, Apache Spark, EMR or Dataproc, Hive, Delta Lake, Presto or Trino, Airflow, and data lineage tools such as DataHub, Marquez or OpenLineage.
- Experience implementing and tuning Spark, Delta Lake and Presto at terabyte scale or beyond.
- Strong understanding of Apache Spark internals (Catalyst, Tungsten, shuffle) with experience customising or contributing to open source code.
- Familiarity with a modern open source and cloud native data stack: Apache Iceberg, Hudi or Delta Lake; Trino, Presto, DuckDB, ClickHouse, Pinot or Druid; Airflow, Dagster or Prefect; dbt, Great Expectations, DataHub or OpenMetadata; Kubernetes, Terraform and Docker.
- Strong analytical and debugging skills for complex issues in large scale systems.
The actual day to day:
- Building and running data infrastructure for a platform handling millions of orders daily.
- Working inside a pod aligned to a business theme, contributing to solution design rather than only implementation.
- The posting says engineers are expected to challenge existing solutions, not just build to spec.
Location and office reality:
- Bangalore. Office days are not stated in the posting.
Honest fit guidance:
- The Spark internals requirement is the real filter. Many candidates have used Spark; far fewer can talk about Catalyst and shuffle behaviour credibly.
- Meesho describes a culture that values speed over perfection and logical debate over authority. That suits some people and not others, and it is worth taking literally.
- The scale numbers in the posting are unusually concrete for an Indian ecommerce role, which makes this a good one for a CV if you want volume experience.
Apply on company site
Opens jobs.lever.co, the employer's own application page. Applying is always free.