Senior Data Engineer

Location- Gurgaon

Type

About the Role

data platform

ETL pipelines and warehouse models

The Ideal Candidate

You’re a generalist with strong data instincts. You care about correctness, performance, and maintainability. You enjoy building systems, understanding data deeply, and connecting the dots across complex data flows. You’re comfortable wearing multiple hats in a fast-moving environment where platform thinking and pragmatism go hand in hand.

Responsibilities

• Help build and evolve the

  core data platform

  , including pipelines and data warehouse layers
• Design and maintain structured datasets to support

  reporting and analytics

• Work with structured and semi-structured data across

  PostgreSQL

  ,

  MySQL

  , and

  MongoDB

• Develop and maintain

  ETL pipelines

  for both raw data and analytics-ready warehouse tables
• Write and optimize complex queries to process

  billions of records

  efficiently
• Perform

  data exploration and mining

  to uncover patterns, inconsistencies, or optimization opportunities
• Write transformation and automation logic using

  Groovy

  or

  Python

• Manage infrastructure across

  on-prem and AWS environments

• Collaborate with engineers, analysts, and product teams to solve business problems with data
• Define and enforce

  data validation

  , audit, and alerting mechanisms

Requirements

• 4–8 years of experience in

  data engineering

  or a related backend/data-heavy role
• Strong SQL skills and deep understanding of

  query performance tuning

• Proficient in

  Groovy

  or

  Python

  for scripting and automation
• Hands-on experience with

  PostgreSQL

  ,

  MySQL

  , and

  MongoDB

  at scale
• Experience working with or building for a

  data warehouse

  (e.g., Redshift, Trino, PostgreSQL)
• Comfortable working in

  cloud (AWS)

  and/or

  on-prem environments

• Experience building and operating production data systems and pipelines
• Strong problem-solving skills and a bias toward ownership and action
• Ability to debug across systems and connect the dots in complex data flows

• Nice to Have

• Experience with

  Apache NiFi

  ,

  Airflow

  , or custom orchestrators
• Exposure to

  data mining

  , anomaly detection, or pattern recognition techniques
• Familiarity with warehouse modeling concepts (fact/dim tables, reporting views)
• Experience with tools like

  Trino

  ,

  AWS Athena

  ,

  Metabase

  , or similar query/BI platforms
• Familiarity with observability practices (monitoring, alerting, logging)
• Exposure to streaming systems (Kafka, Spark, Flink)
• Experience supporting

  compliance or finance-focused

  data workflows
• Comfort working in containerized setups (Docker/Kubernetes)

• Why Join Us?

• Work on

  core data infrastructure

  with direct business impact
• Join a

  lean and collaborative team

  were engineers shape direction
• Get deep ownership of architecture, tooling, and design
• Solve meaningful data problem at scale in a

  fast-moving startup