(aws) Data Engineer

Job Summary

Join - Innovating Healthcare with AI and Data. Client is revolutionizing the U.S. healthcare revenue cycle market by blending cutting-edge AI with human expertise. Since 2011, we’ve grown rapidly, partnering with over 500 healthcare providers, including top-tier hospitals and diagnostic labs. Our Mumbai, Bangalore and Pune offices build the technology that drives these solutions.

About The Role

We are looking for a Senior Data Analyst who will play a critical role in designing, building, and scaling data solutions across our products and client implementations. As a Senior Data Analyst, you will work closely with Product, Engineering, Data Science, and Client-facing teams to translate complex business and healthcare use cases into robust, scalable data models and pipelines. You will be expected to mentor junior analysts, influence data design decisions, and ensure data quality, reliability, and performance at scale.

Role & Responsibilities

• Own the design, development, and operation of scalable data pipelines across structured and unstructured data sources.
• Build and optimize ETL/ELT workflows using SQL, Python, PySpark, and AWS big data technologies.
• Define and enforce data quality, validation, and monitoring standards to ensure accuracy and trust in data.
• Perform advanced data exploration and analysis to solve ambiguous business problems and deliver actionable insights.
• Act as a senior data owner during product and client implementations, ensuring data use cases are correctly implemented, tested, and production-ready.
• Collaborate with Product, Engineering, and Data Science teams on data architecture and analytical use cases.
• Provide technical leadership and mentorship to junior analysts and contribute to data platform best practices.

Required Skills & Experience

• 4+ years of experience in Data Analytics / Data Engineering roles.
• Strong expertise in SQL and hands-on experience with relational and NoSQL databases.
• Advanced experience with Python and PySpark for large-scale data processing.
• Proven experience building & managing ETL pipelines using tools such as Airflow, AWS Glue, or similar.
• Strong understanding of data modeling and performance optimization.
• Experience working with AWS data services (S3, EMR, Redshift, Athena, RDS, etc.).
• Ability to own complex data problems end-to-end and influence cross-functional stakeholders.
• Exposure to US healthcare data is a strong plus.