Raapid Inc
From Raapid Inc's careers page
Status: listed on the employer's own careers page when we last checked (daily). Confirm on their site before applying.
You'll bring strong hands-on experience in SQL, ETL processes, and data pipeline development.
RAAPID is a leading healthcare technology innovator specializing in AI-enabled risk adjustment solutions. Funded by Microsoft and Great Place to Work-certified organization, we serve payers, healthcare providers, and support organizations with cutting-edge technology solutions that optimize revenue, ensure compliance, and reduce administrative costs.
Backed by Microsoft: Proudly funded by M12, Microsoft's venture fund, validating our technology innovation and market potential
Industry Pioneer: Leveraging state-of-the-art artificial intelligence, machine learning, vision AI, and knowledge graphs to transform healthcare operations
Strong Foundation: Built on four key pillars - Trust, Technical Competence, Stability, and Technical Innovation
Recognition: Proud recipient of HITRUST certification, demonstrating our commitment to security and compliance
Culture: Certified Great Place to Work, reflecting our dedication to employee satisfaction and professional growth
Mission-Driven: Focused on revolutionizing value-based healthcare through customizable, AI-powered solutions
Global Presence: Headquartered in Louisville, Kentucky, with a robust team of over 100 employees across the US and India
Job Summary
We're hiring a Senior Data Engineer for Ahmedabad Location who doesn't just move data from Point A to Point B - but someone who looks at a raw, messy dataset and instinctively asks "wait, what's hiding in here?" Someone who finds patterns before anyone knew there was a pattern to find. Someone who, at a dinner party, has to actively stop themselves from explaining why that restaurant's ordering system is probably not indexed correctly.
If your idea of a good time is untangling a spaghetti ETL pipeline, writing a stored procedure so clean it could double as poetry, or spotting an anomaly in a dataset that everyone else walked right past - we'd like to talk.
You'll bring strong hands-on experience in SQL, ETL processes, and data pipeline development. You'll write complex queries that don't just work - they're fast, readable, and something your future self won't curse at six months later. You'll build scalable pipelines that handle large, real-world healthcare data without flinching, and use Python and PySpark when the data gets big enough that a single machine starts to feel personally offended.
But beyond the technical craft - you're someone who genuinely loves data. Not in a screensaver way. In a "give me 10 minutes with this dataset and I'll tell you three things nobody asked for but everyone needed to know" kind of way.
If data is your native language and pipelines are your playground - let's build something together.
Develop and maintain complex SQL queries, stored procedures, and database objects.
Perform query optimization and performance tuning for large and complex datasets.
Design, develop, and maintain ETL pipelines for data extraction, transformation, and loading.
Process and transform large datasets using Python/Java and PySpark.
Work closely with engineering, analytics, and product teams to understand and deliver data requirements.
Ensure data quality, consistency, and reliability across systems.
Automate data workflows and data processing tasks.
Troubleshoot and resolve database and data pipeline performance issues.
Bachelor’s degree in Computer Science, Information Technology, or a related field.
Required Skills
Leverage GenAI and Agentic AI to automate day to day task
Strong experience in MySQL including complex joins, subqueries, window functions, and stored procedures.
Hands-on experience in SQL performance tuning and query optimization.
Experience in ETL development and data pipeline building.
Proficiency in Python for data processing and scripting.
Good understanding of database design, indexing, and data modeling.
Experience handling large datasets and data transformations.
Knowledge of data warehousing concepts and big data processing.
Familiarity with cloud platforms such as AWS, Azure, or GCP.
Experience working with data analytics or reporting systems.
Experience with PySpark for distributed data processing.
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