Edu Intelligence is a UK-based edtech venture building edu-intelligence.ai a data-driven platform that turns fragmented school and trust data into actionable insight for education leaders. We are at an early but exciting stage: our modern data stack is being built now, and we need a talented engineer to own and grow the pipelines that power everything.

The Role

We are looking for a Data Engineer based in India to join us as a core member of our small, distributed team. You will be hands-on with our ETL/ELT layer every day, building and maintaining the pipelines that feed edu-intelligence.ai.

You will:

Design, build and maintain ELT pipelines using Airbyte (extraction), Airflow on Astronomer/Astro (orchestration), and dbt (transformation)
Model, transform and test data in BigQuery, ensuring it is clean, documented and trusted
Help develop and maintain a semantic layer (Cube Cloud) so stakeholders and our AI layer can query reliable, governed metrics
Monitor pipeline health, set up alerting, and troubleshoot failures quickly
Work with messy, real-world education data school MIS exports, API feeds and make it usable
Collaborate closely with our product teams (UK-based) to understand what data is needed and in what shape
Contribute to our data documentation, lineage tracking and quality framework
Help shape our data architecture as the platform scales

Our Stack

Extraction - Airbyte (Self Hosted)
Orchestration - Apache Airflow on Astronomer (Astro)
Transformation - dbt (Core)
Warehouse - Google BigQuery
Semantic Layer - Cube (Cloud)
Version Control -Git / GitHub
Hosting/Cloud- Google Cloud Platform (GCP)

What We Need From You

Essential:

3+ years of hands-on data engineering experience building production pipelines
Strong SQL skills you think in SQL and can write complex, performant queries
Practical experience with at least two of: Airbyte, Airflow, dbt, BigQuery
Understanding of ELT/ETL patterns, data modelling (dimensional, wide-table, etc.) and data quality testing
Experience with Git-based workflows and CI/CD for data pipelines
Comfortable working with Python for scripting, custom operators or lightweight transformations
Excellent written English you will communicate daily with a UK-based team via Slack, Loom, and calls
Self-motivated and comfortable working independently in a small, distributed team
Overlap with UK hours: able to work 8 hours per day, with a core hours between 8:00 AM 3:00 PM GMT (1:30 PM 8:30 PM IST) and your additional hours before or after this time.

Highly Desirable:

Experience with Cube, LookML, or another semantic layer tool
Familiarity with GCP services (BigQuery, Cloud Storage, Cloud Functions, Pub/Sub)
Experience with Astronomer / Astro for managed Airflow
Knowledge of data contracts, data cataloguing, or data governance practices
Exposure to education-sector data (MIS systems like SIMS, Bromcom, Arbor; DfE data; census data)

Nice to Have:

Experience integrating data pipelines with AI/ML workflows or LLM-based products
Understanding of semantic/metrics layers and how they serve BI tools and AI applications
Familiarity with Terraform or infrastructure-as-code for GCP resources

What We Offer

Fully remote role work from anywhere in India
Competitive salary benchmarked above Indian market rate for a UK-funded startup
Dedicated training budget and time for professional development
Direct access to the founder and CEO your voice matters
The chance to build something meaningful from the ground up in a mission-driven edtech company
Flexible working around core overlap hours
Performance-related bonus opportunity (dependent on company and individual performance)

How to Apply

Apply via Linkdin with your CV and a short cover note explaining why this role excites you and which parts of our stack you have the most experience with. You will be asked screening questions please answer them thoughtfully, as they are used to shortlist candidates.

Edu Intelligence is committed to building a diverse team. We welcome applications from all backgrounds.

Slaary: Dependent on expereince, 80k-110k INR per month.

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