Senior Data Engineer - Legacy Database Modernization

Senior Data Engineer - Legacy Database Modernization About Ajentica Ajentica is an AI-native product engineering company helping ambitious software businesses become truly agentic. We partner with growth-stage and private-equity-backed companies to modernize complex platforms, redesign operational workflows and build intelligent systems that work alongside people not merely generate content. Our work spans agentic automation, enterprise software modernization, intelligent product development and AI-enabled delivery across healthcare, pharmacy, compliance, HR technology and other operationally complex industries.

From HIPAA-sensitive clinical workflows and autonomous desktop agents to platform integration and AI-assisted software development, we focus on moving AI beyond prototypes and into secure, measurable and production-ready systems. Job description Ajentica is leading a backend data rebuild for a behavioral health platform built on ~20 years of accumulated technical debt. The current system: Transformation logic buried across MSSQL stored procedures Heavily patched over time No formal ERDs or structured data model This is not a maintenance role.

This is a ground-up re-architecture & migration of the data layer . We are looking for someone who can step into ambiguity, reverse engineer reality, and architect a clean, scalable foundation. Youll develop Python-based data migration and transformation pipelines for moving and reshaping legacy MSSQL data into a redesigned Postgres model.

WHAT YOU’LL BE DOING Reverse engineer existing stored procedures, transformation logic, and schema behavior Map what the system is actually doing vs. intended behavior Build current-state ERDs (from scratch) Design a clean, maintainable target data model (Postgres as target, migrating from MSSQL) Deconstruct and rationalize the transformation layer: Identify and remove dead logic Consolidate redundant transformations Simplify pipelines and flag issues or inconsistencies Retrofit missing capabilities into the redesigned schema Develop Python-based ETL pipelines Orchestrate workflows using Azure Data Factory Migrate the actual data and validate end-to-end post-migration. Ensure clear documentation and traceability across all components CORE REQUIREMENTS 4 - 7 years of experience in software engineering, primarily in data engineering Strong relational data modelling experience, including redesigning or migrating an existing production database - not solely greenfield warehouse/lakehouse modelling. Proven ability to reverse engineer undocumented systems Deep hands-on experience working with MSSQL / SQL Server databases Extensive experience building ETL pipelines in Python Working knowledge of Postgres Experience with Azure Data Factory Familiarity with .NET-integrated environments Ability to make and defend architectural decisions with confidence High attention to detail and strong reasoning and analysis skills Strong English communication skills NICE TO HAVE BTech CSE from an IIT/NIT/Tier 1 institution and/or experience in a leading company Exposure to modern data stacks (data lake, parquet, etc.) Awareness of AI/ML-ready data modeling practices WHAT YOU DON’T NEED Domain expertise in behavioral health Scrum leadership or team management experience Big data / distributed systems expertise WHO THIS IS FOR This role is for someone who has done this before: Walked into a messy, undocumented system Figured out how it actually works Rebuilt it into something clean, structured, and scalable