- Data Engineer

You should apply if you have:

2–3 years of experience as a Data Engineer, Analytics Engineer, or in a similar data-platform role.

Strong SQL and Python, with the ability to build, debug, and optimize production data pipelines.

Hands-on experience with a cloud data stack — AWS preferred (S3, Glue, Redshift) — and modern ELT tooling.

Experience ingesting data from diverse sources (transactional databases, SaaS APIs, file dumps) into a warehouse or lakehouse.

Exposure to transformation frameworks like dbt and orchestration tools (Airflow, Glue, or similar).

A reliability mindset — you care about data freshness, quality, monitoring, and infrastructure cost.

The ability to work independently and own systems end-to-end in a build-from-scratch environment.

An AI-first mindset and comfort using AI tools (Copilot, Claude, etc.) to accelerate engineering work.

You should not apply if you:

Prefer working only on well-defined tickets over designing systems from scratch.

Are uncomfortable owning production pipelines, reliability, or debugging messy real-world data.

Need constant direction and struggle with ambiguity or greenfield problems.

See data engineering as just "moving data" rather than enabling business decisions.

Are resistant to feedback, learning new tools, or leveraging AI to improve your productivity.

Prefer babysitting legacy jobs over building scalable, automated, version-controlled pipelines.

Are uncomfortable with cost and ownership accountability in a fast-paced, high-growth environment.

Don't enjoy collaborating with analysts and stakeholders to understand what the data is for.

Are looking for a narrow role rather than one that demands ownership, curiosity, and continuous improvement.

Skills Required

Technical Skills

Advanced SQL (joins, CTEs, window functions, query optimization, aggregations)

Python for data pipelines and automation

Cloud data platforms — AWS (S3, Glue, Redshift) preferred

ELT/ETL design and orchestration (Airflow, Glue, or similar)

Data lakehouse concepts — S3 / Apache Iceberg (good to have)

dbt and data modeling (preferred)

Data ingestion from RDBMS, APIs,



and file sources; managed connectors like Fivetran (good to have)

Data quality, testing, and freshness/uptime monitoring

Version control and CI/CD for data workflows (Git)

Understanding of data warehousing and dimensional modeling Business & Analytical Skills

Strong problem-solving and systems thinking

Ability to translate analytics and business needs into reliable data models and pipelines

Cost-awareness — right-sizing compute and storage

Comfort collaborating across analysts, engineers, and business stakeholders

Experience working with D2C, E-commerce, Retail, or Consumer business data (preferred)

What will you do?

Build and own the ingestion layer — land core sources (RDS, Vinculum, Tally, marketplaces) reliably into our S3-Iceberg Bronze lakehouse.

Stand up and maintain a multi-tool EL stack (AWS Glue for native/file sources, Fivetran for marketplace connectors) plus pipeline orchestration.

Design the medallion architecture (bronze / silver / gold) foundation together with the Analytics Engineers.

Ensure data freshness, reliability, and quality through monitoring and alerting.

Migrate legacy stored-procedure jobs into version-controlled, tested, maintainable pipelines.

Optimize infrastructure cost — inventory jobs, close idle compute, and right-size storage.

Partner with Analytics Engineers and Analysts to make clean, governed data available for modeling and reporting.

What success looks like

During your first six months, you'll:

Have all critical (P0) sources landing daily in the Bronze lakehouse with defined freshness SLAs.

Stand up the medallion schemas and Redshift↔Iceberg read path, with dbt running from Git on production.

Put freshness and failure alerting in place across every pipeline you own.





Retire idle and duplicate jobs, with a documented monthly cost saving.

Deliver a reliable data foundation that unblocks the entire analytics roadmap.

Work Experience: 2–3 years

Working days: Monday - Friday

Location: Golf Course Road, Gurugram, Haryana (Work from Office)

Perks

Friendly atmosphere

High learning & personal growth opportunity

Flexible Timings

Diverse work setting

Why Nutrabay

We believe in an open, intellectually honest culture where everyone is given the autonomy to contribute and do their life’s best work. As a part of the dynamic team at Nutrabay, you will have a chance to learn new things, solve new problems, build your competence and be a part of an innovative marketing-and-tech startup that’s revolutionising the health industry.

Working with Nutrabay can be fun, and a place of a unique growth opportunity. Here you will learn how to maximise the potential of your available resources. You will get the opportunity to do work that helps you master a variety of transferable skills, or skills that are relevant across roles and departments.

You will be feeling appreciated and valued for the work you delivered. We are creating a unique company culture that embodies respect and honesty, which will create more loyal employees than a company that simply shells out cash. We trust our employees and their voice and ask for their opinions on important business issues.

About Nutrabay

Nutrabay is the largest health & nutrition store in India. Our vision is to keep growing, have a sustainable business model, and continue to be the market leader in this segment by launching many innovative products. We are proud to have served over 1 million customers uptill now, and our family is constantly growing.

We have built a complex and high-converting eCommerce system, and our monthly traffic has grown to a million. We are looking to build a visionary and agile team to help fuel our growth and contribute towards further advancing the continuously evolving product.

Funding

We raised $5 million in a Series A funding.

📌 Data Engineer (Gurugram)
🏢 Nutrabay
📍 Gurugram