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.
