Data Engineer

Meesho · Bengaluru

  • Experience3–7 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelmid
  • Posted10 Sept 2026
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About Meesho

Meesho is hiring in Bengaluru in ecommerce retail. This role looks for around 3+ years of experience.

Skills

  • Python
  • SQL
  • Pandas
  • Polars
  • DBT
  • DuckDB
  • Airflow
  • Dagster
  • Prefect
  • Snowflake
  • PostgreSQL
  • MSSQL
  • Databricks
  • Delta Lake
  • Auto Loader
  • AWS
  • Azure
  • GCP
  • ETL/ELT pipelines
  • event-driven ETL architectures
  • data engineering
  • workflow orchestration
  • LLM APIs
  • prompt engineering
  • AI-assisted development tools

The role

A data engineer at a large e-commerce marketplace builds data pipelines with Python and SQL, applies data engineering and ETL/ELT pipelines to analytics systems, and develops AI agents and LLM APIs for data workflows. Work includes workflow orchestration tools and cloud-native data solutions.

Full job description

Responsibilities:

Design, develop, and maintain production-grade ETL/ELT pipelines for large-scale data processing.

Build reliable and scalable data workflows using orchestration tools such as Airflow, Dagster, or Prefect.

Develop efficient data transformation and analytics workflows using Pandas, Polars, DBT, and DuckDB.

Work with event-driven and event-based ETL architectures for real-time and asynchronous data processing.

Design and optimise data models across databases such as Snowflake, PostgreSQL, MSSQL, and similar technologies.

Build resilient data pipelines using Databricks, Delta Lake, Auto Loader, and workflow orchestration.

Develop cloud-native data solutions across AWS, Azure, or GCP.

Implement data quality checks, monitoring, observability, and pipeline reliability mechanisms.

Leverage AI tools such as Claude, GitHub Copilot, and similar tools to accelerate software development and improve engineering productivity.

Explore and implement LLM-based solutions, AI agents, and AI-powered automation for data engineering workflows.

Work with technologies such as LangGraph, Claude Code, LLM APIs, and prompt engineering where applicable.

Collaborate with product, engineering, data science, and other cross-functional teams in a distributed work environment.

Troubleshoot complex data and engineering problems and develop scalable, maintainable solutions.

Contribute to technical strategy, architecture decisions, and product roadmap discussions.

Requirements:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

3+ years of software engineering experience, with a strong focus on data engineering.

Strong programming skills in Python and SQL.

Hands-on experience with Pandas and/or Polars.

Experience building production-grade ETL/ELT pipelines.

Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect.

Hands-on experience with DBT and DuckDB.

Understanding of event-based/event-driven ETL architectures.

Strong knowledge of database technologies and the ability to select the right database for different use cases.

Experience with one or more of Snowflake, PostgreSQL, MSSQL, or similar databases.

Strong problem-solving skills with the ability to work effectively in ambiguous environments.

Excellent communication and collaboration skills.

Genuine curiosity and passion for AI and its applications in data engineering.

Experience using AI-assisted development tools such as Claude, GitHub Copilot, or similar platforms.