Data Engineer

Data Engineer (2+ Exp)
SQL / Python / Pipelines | Visualization | dbt a Plus | Remote
About Make A Difference (MAD)
Vision: End Poverty in Our Lifetime.
For 18 years, Make A Difference (MAD) has been rewriting the future for children in need of care and protection, working with thousands of young leaders across 13+ states in India. We measure success in stable, middle-class adult outcomes — because breaking the cycle of poverty isn't enough. We're here to shatter it forever.
Role Overview
The Data Engineer owns the layer between MAD's software and MAD's decisions. MAD runs several systems, and each one holds a fragment of a child's journey. You'll build the pipelines and data models that turn scattered system data into answers — and the dashboards that put those answers in front of the people making the calls.
You will report to the Director of Technology and work alongside the developer who owns the source systems, and with program and monitoring teams who use what you build.
Key Responsibilities
Build, maintain, and evolve pipelines that bring data from MAD's operational systems into the warehouse
Own transformation logic that turns raw system data into reporting-ready models
Design and maintain data models that are clean, documented, and stable as upstream schemas change
Build and maintain the dashboards MAD runs on, working directly with program and monitoring teams
Build monitoring and alerting so pipeline failures surface automatically
Reconcile discrepancies across systems and hold the definition of MAD's core metrics
Maintain a data dictionary and pipeline documentation that others can read without a walkthrough
What We're Looking For
Experience building and running data pipelines that other people depend on — on real data, not just in a course
Strong SQL and comfort with relational databases — complex queries, performance, schema design
Experience designing data models that a reporting layer can sit on
Experience building and running ETL/ELT pipelines and orchestration
Python for data work — transformation, scripting, automation
Comfortable working with APIs as data sources and event-driven data flows
Able to work with any visualization/BI tool — Metabase, Superset, Looker, Power BI, Tableau, or similar; no single tool required
dbt experience is a strong plus; equivalent transformation-layer experience also works
Open to adjacent experience — analytics engineering, BI development, or similar data-stack backgrounds are all welcome
Working Style
Curious about the decision behind the request, not just the metric being asked for
Takes ownership of pipeline health, not just pipeline delivery
Strong documentation habits — you write things down so the system isn't in your head
Comfortable working independently and flagging blockers early in a remote setting
Can explain a data limitation to a non-technical team without jargon or condescension
Compensation & Logistics
CTC: ₹8.5–10 lakhs per annum, based on experience
Location: Remote, with periodic travel to team hubs
Type: Full-time
Recruitment Process
Stage 1: Application
Submit your CV with the job role as the subject line.
Stage 2: Resume Screening
Shortlisted candidates will receive a pre-work exercise.
Stage 3: Pre-work
Complete and return the pre-work within 3 days of receiving it.
Stage 4: Pre-work Debrief
A 20–30 minute debrief call with the hiring manager to discuss the pre-work and the candidate’s approach.
Stage 5: Virtual Immersion
A 1-day virtual immersion (approximately 10 hours) involving multiple interactions with the MAD team. This is an important part of the selection process and is designed to give both the candidate and the team a realistic understanding of the role and working environment. Please apply only if you are willing to commit to the full immersion.
Stage 6: Final Decision
If the immersion goes well, the final offer will be made within 48 hours.

Work arrangement
No