Data Engineer

Job Description - 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 environment

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.