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Data Analytics Engineer
We Want To Change The World. We Believe It Starts With Education.
In India, 100 million children from low-income communities grow up without access to the 21st-century skills they need to thrive, from emotional intelligence and digital literacy to everyday money management. This gap leads to a lifetime of limited opportunity, intergenerational poverty, and rising mental health concerns.
What Are We Doing?
India's classrooms are stuck in the past. We're building what kids need for the future.
At The Apprentice Project (TAP), we reach students where they already are: on WhatsApp. Through our chatbot, students learn through hands-on projects and build skills that last.
Every one of those interactions generates data: who registered, who returned, what content reached them, and what they did with it. Today that data comes from many sources and is often messy. To answer the questions that shape our programs, we need data that is clean, connected and trustworthy.
That's where you come in.
As our Analytics Engineer, you'll be the first hire on the Data team and will own TAP's data layer end to end: the pipelines that bring data in, the models that make it usable, the systems that keep it clean, and the answers that help our teams act.
This isn't just backend work. It's infrastructure that fuels impact.
Who We're Looking For
A builder who hates doing the same thing twice. You see a messy spreadsheet and think about how to stop it from ever arriving messy again. You're as comfortable tracing why 2,000 students didn't receive their course material as you are writing a dbt model, and you use AI tools to get there faster without giving up rigour.
If you want to own a data function from the ground up and grow into leading it, we want to meet you.
About The Role
Location: Remote (India)
Experience: 2–4 years of relevant experience
Compensation: ₹8–10 LPA
Reports to: Associate Senior Manager - Data & MEAL
Type: Full-Time
Tech Stack: SQL, dbt, BigQuery (GCP), Python, Git/GitHub, Glific (WhatsApp chatbot platform), GenAI coding assistants
What You'll Do
Data Pipelines & Modelling
  • Own and maintain our ETL/ELT pipelines into BigQuery, including chatbot (Glific/WhatsApp) data, registration data and partner records.
  • Build, test and document dbt models that give teams a single, trusted view of students across years, cohorts and programs.
  • Handle scheduling, orchestration, failures and backfills, so pipelines run reliably without manual babysitting.
Data Cleaning & Clean-Data Systems
  • Clean, standardise and reconcile data from multiple sources: deduplicate records, match students across years and sources, and fix inconsistent phone numbers, names, schools and cohort identifiers.
  • Go beyond cleaning: build systems that produce clean data by default, such as validation at ingestion, standard formats, controlled inputs for forms and sheets, and clear data entry guidelines for the teams that send us data.
  • Maintain lineage and documentation so everyone knows where a number came from and how far to trust it.
Monitoring & Reliability
  • Set up data quality tests and monitoring for freshness, completeness and anomalies, so problems are caught by alerts, not by users.
  • Investigate delivery gaps, such as students who didn't receive messages or material, by tracing the problem through bot flows, data and pipelines, then fixing the root cause.
Answering Questions That Drive Decisions
  • Answer data questions from program and leadership teams, such as returning-student counts, cohort and retention analysis, and content delivery gaps, quickly and with clear explanations.
  • Build and maintain the dashboards and recurring reports teams rely on, and automate them wherever possible.
Automation & AI-Driven Efficiency
  • Treat every repeated task as a candidate for automation: recurring pulls, reports, checks and fixes.
  • Use GenAI tools as part of your daily workflow to write and review SQL and dbt code, generate tests and documentation, and debug faster, while verifying everything they produce.
  • Explore AI-assisted approaches to hard data problems, such as fuzzy matching of student and school names, or classifying free-text responses.
Building the Function
  • Keep code version-controlled, reviewed and documented, so TAP's data never depends on one person.
  • Work with the Data & MEAL lead to shape the data roadmap, set standards, and eventually onboard and mentor the next hires.
Who You Are
  • You have 2–4 years of hands-on experience in data engineering, analytics engineering or a closely related role.
  • You write strong SQL and have solid dbt experience: models, tests, documentation and incremental builds.
  • You've run production pipelines, including scheduling, monitoring, error handling and backfills, on BigQuery or a comparable cloud warehouse.
  • You've cleaned messy, real-world data from multiple sources, including deduplication and entity matching, and you've built checks to stop it recurring.
  • You use Python for pipelines, cleaning and automation, and you're fluent with Git/GitHub, including code review.
  • You use GenAI tools to work faster, and you know where they fail and how to check their output.
  • You write clearly: you can explain what broke, what you did, and what it means to someone non-technical.
  • You take ownership: you notice problems before others do and see work through to the end.
  • You're excited about applying data engineering to education, equity and social impact.
Good to Have
  • Experience with Glific, WhatsApp or other chatbot or messaging data.
  • Contributions to open-source projects, or code written to open-source standards.
  • Dashboard experience (Looker Studio, Metabase or similar).
  • Familiarity with basic statistics and A/B test analysis.
  • Experience in education or the social sector.
Why Join Us?
Because you won't just maintain someone else's data stack. You'll build it.
At TAP, data decides which students we reach, what content they receive, and whether our programs actually work. As our first data hire, you'll create the foundation that makes those decisions possible, and you'll grow with it.
What You Can Expect?
  • Real ownership: You'll own TAP's data layer end to end from day one.
  • Bold challenges: Turn messy, multi-source data on lakhs of students into a system the whole organisation trusts.
  • Cross-functional collaboration: Work with program, product and leadership teams.
  • Remote flexibility: Work from anywhere, create impact everywhere.
  • Growth path: A clear path to Senior Analytics Engineer or Data Lead as the team grows.
  • Clarity and transparency: A values-driven culture with honest, direct feedback.
You can always reach out to us with any questions at hr@theapprenticeproject.org

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