Data Engineer - Seller Operations

Job Title: Data Engineer, Seller Operations

Location: Gurgaon, India

About noon

Were building an ecosystem of digital products and services that power everyday life across the Middle Eastfast, scalable, and deeply customer-centric. Our mission is to deliver to every door every day. We want to redefine what technology can do in this region, and were looking for a Data Engineer who can help us move even faster.

noons mission: Every door, every day.

What you'll do:

Team noon has some of the fastest, smartest, and hardest-working people we've encountered. With a young, aggressive, and talented team, we're driving major missions forward.

As a Data Engineer you will design, build, and maintain robust data pipelines to support seller performance and operational analytics. The role ensures reliable, scalable data infrastructure, enabling accurate reporting and real-time insights for business and product teams. The role will collaborate closely with analytics, product, and operations to optimize data quality and drive data-led decision-making across seller operations.

Key Responsibilities:

You will:

• Design, build, and maintain end-to-end data pipelines for Seller Ops use cases (onboarding, performance, fulfillment, returns, SLA tracking).
• Develop and manage ETL/ELT workflows to ingest data from multiple sources (transactional systems, APIs, logs, third-party tools).
• Create and optimize data models and marts to support analytics, dashboards, and self-serve reporting.
• Ensure data quality, accuracy, and reliability through validation, monitoring, and alerting.
• Work closely with Analytics and Product teams to understand data requirements and enable faster insights.
• Optimize query performance and storage costs across data platforms.
• Implement and maintain data governance, documentation, and access controls.
• Support experimentation and product analytics by enabling clean, well-instrumented datasets.
• Troubleshoot pipeline failures and resolve data issues with minimal downtime.

Requirements:

• 34 years of experience as a Data Engineer or similar role.
• Strong proficiency in SQL and experience with data modeling (fact/dimension tables).
• Hands-on experience with ETL/ELT tools (Airflow, dbt, Talend, Fivetran, or similar).
• Experience with data warehouses (BigQuery, Snowflake, Redshift, Hive, etc.).
• Familiarity with cloud platforms (AWS / GCP / Azure).
• Experience handling large-scale, structured and semi-structured datasets.
• Good understanding of data reliability, pipeline monitoring, and best practices.
• Exposure to streaming data (Kafka, Kinesis, Pub/Sub).
• Experience with Seller Ops, marketplace, or supply-side data.

Who will excel?

• Were looking for people with high standards, who understand that hard work matters.
• You need to be relentlessly resourceful and operate with a deep bias for action.
• We need people with the courage to be fiercely original.
• noon is not for everyone; readiness to adapt, pivot, and learn is essential.