SDE 3 - Data Platform

Meesho · Bengaluru

  • Experience4–7 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelmid
  • Posted2 Sept 2026
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About Meesho

Meesho is hiring in Bengaluru in ecommerce retail. This role looks for around 4+ years of experience.

Skills

  • ETL/ELT
  • Apache Kafka
  • Apache Spark
  • Apache Flink
  • Python
  • Java
  • Go
  • SQL
  • Airflow
  • dbt
  • batch data processing
  • streaming data processing
  • relational databases
  • NoSQL databases
  • cloud platforms
  • data modeling
  • monitoring
  • alerting
  • logging
  • automated testing
  • data governance

The role

A data platform engineer at an ecommerce marketplace builds scalable pipelines and data infrastructure using Apache Spark, Apache Kafka, and Apache Airflow, enabling analytics and product teams. The role also applies data modeling and SQL to support reliable batch and streaming systems.

Full job description

We are seeking a skilled Data Platform Engineer to build and scale reliable data infrastructure and pipelines. You will enable analytics, product, and business teams by ensuring high-quality, performant, and accessible data across the organization.

The core responsibilities for the job include the following:

Data Platform and Pipelines:

Build and maintain ETL/ELT pipelines for structured and unstructured data.

Design, develop, and optimize batch and streaming pipelines using tools such as Kafka, Spark, or Flink.

Ensure data integrity, availability, and performance across data systems.

Design and optimize data models for analytics and product use cases.

Backend and Data Engineering:

Write clean, maintainable, production-grade code (preferably Python, Java, Go, or Ruby) to support: Data workflows, Internal data services, Integrations and automation

Build internal tooling to improve data reliability and developer productivity.

Collaboration and Delivery:

Partner with product, analytics, and engineering teams to define data needs and infrastructure requirements.

Contribute to cross-functional system design discussions and architectural reviews.

Ensure delivery of reliable infrastructure and data solutions that meet SLAs.

Quality and Best Practices:

Implement monitoring, alerting, and logging for data pipelines.

Write automated tests for data transformations and pipeline logic.

Drive best practices for scalability, cost efficiency, and data governance.

Requirements:

4-6 years of experience in data platform or data engineering roles.

Strong proficiency in SQL and experience with relational and NoSQL databases.

Hands-on experience with Airflow, DBT, Spark, or Flink.

Experience with streaming or batch data processing systems.

Proficiency in at least one programming language (Python, Go, or Java).

Familiarity with cloud platforms (AWS, GCP, or Azure).

Nice to Have:

Experience with real-time streaming (Kafka, Kinesis, Pub/Sub).

Exposure to data warehouses (Snowflake, BigQuery, and Redshift).

Experience operating data platforms in high-scale or fintech domains.

Understanding of data security, privacy, and compliance.