Data Engineer

About Us

Visit Health is a pioneering health-tech platform, founded in 2016 by BITS Pilani alumni, dedicated to making healthcare accessible, affordable, and preventive. Originated as a telemedicine platform during the 2015 Swine Flu epidemic, Visit Health has grown into an all-in-one wellness ecosystem that connects doctors, insurers, and millions of Indian families. Our services range from physical and mental wellness to OPD benefits, empowering both individuals and corporations to prioritize well-being.

We are looking for a Data Engineer to join our high-energy team

As part of your day-to-day work, you will:

• Design, build, and maintain robust data pipelines to support data ingestion, transformation, and standardization across multiple source systems.
• Develop and manage data warehouse schemas, ensuring data integrity, consistency, and alignment with product and business requirements.
• Collaborate with stakeholders to identify, define, and revise reporting and analytical requirements.
• Develop reports, dashboards, and data analyses that maintain data sanity and surface actionable insights for business decision-making.
• Visualize data effectively using graphs, infographics, cohort analyses, heat maps, clustering, and other techniques suited to the audience and use case.
• Evaluate and monitor changes to upstream production systems, assessing downstream impact and implementing necessary pipeline updates.

Must-Haves:

• 2–5 years of hands-on experience in data engineering or a closely related role.
• Strong proficiency in SQL with working knowledge of relational databases such as MySQL — including stored procedures, functions, indexing, schema design, and relationship management.
• Hands-on experience with AWS services and Amazon Redshift, including a solid understanding of columnar vs. row-based storage, joins, CTEs, primary and foreign keys, schema modeling, and query execution plan analysis and optimization.
• Advanced Python proficiency across two key areas: (a) data analysis using libraries such as Pandas, Polars, NumPy, and Lambda functions on extracted datasets, and (b) data ingestion and extraction workflows using database connections, connection pooling, and ORM/abstraction layers.
• Experience with at least one data visualization or BI tool such as Amazon QuickSight, Tableau, or Power BI.
• Solid understanding of data warehousing concepts and ETL/ELT design patterns.
• Proficiency in Microsoft Excel for ad hoc analysis and reporting.
• Strong analytical and problem-solving skills with the ability to evaluate existing tools and databases and recommend improvements or alternatives.
• Familiarity with data addressing, metadata standards, and data governance principles.
• Excellent written and verbal communication skills, with the ability to work effectively with both technical and non-technical stakeholders.