About the role

Digitxl is building to turn raw analytics into automated diagnostics, reporting, and activation for our marketing, CRO, and analytics clients.

We're looking for an AI & Data Engineer to help design, build, and operate this platform end-to-end: from cloud infrastructure and data pipelines through to the AI agents that turn numbers into plain-English answers our clients actually use. This is a hands-on, build-from-zero role with a clear technical roadmap already scoped - you'll be shaping how it's implemented, not just following a spec.

What you'll be doing

Platform & infrastructure

- Design and operate our GCP environment (BigQuery, Cloud Run, Cloud SQL, Secret Manager, Cloud Scheduler) across production and staging
- Build and maintain the multi-tenant architecture that maps each client to their GA4 property, BigQuery dataset, and usage limits
- Implement IAM, dataset-level access controls, and audit logging to keep client data properly isolated and secure
- Set up CI/CD (GitHub Actions), monitoring/alerting, backups, and disaster-recovery processes so the platform can be trusted to run unattended

Data engineering

- Build and maintain dbt models that turn raw GA4 BigQuery exports into clean, standardised tables
- Build a schema drift detection system that catches client-side tracking changes before they silently break downstream reporting
- Integrate additional data sources over time - Shopify (via Airbyte), Google Ads/Meta Ads, Search Console, PageSpeed Insights, session-quality tools (e.g. Microsoft Clarity), and error tracking (e.g. Sentry)
- Handle the messy realities of production data: export lag, late-arriving data, property migrations,



and identity resolution across systems

AI / MCP tooling

- Design and build MCP tools (Node.js + the MCP SDK) that expose analytics functions - reporting, diagnostics, funnel analysis, attribution comparison to Claude
- Build deterministic diagnostic pipelines (e.g. compare-and-rank breakdowns) that feed clean, structured data to Claude for narrative generation, keeping the AI's role tightly scoped to interpretation rather than calculation
- Write and version the prompts driving automated reporting and diagnostic narratives, with an eye on accuracy, tone, and auditability
- Build and maintain scheduled agent workflows (Cloud Run + Cloud Scheduler) that generate automated client reports, with human review steps built in

Reliability & governance

- Enforce usage limits and cost guardrails across BigQuery queries and Claude API usage
- Maintain client onboarding/offboarding runbooks and support our data handling/DPA obligations
- Contribute to a testing culture - staging environments, automated tests, and safe promotion to production

What we're looking for
- Solid experience with Node.js and building/consuming APIs
- Hands-on experience with Google Cloud Platform
- BigQuery, Cloud Run, Cloud SQL, IAM, Secret Manager (or equivalent experience on another major cloud provider)





- Comfort writing and optimising SQL , ideally with some exposure to dbt or similar transformation tooling
- Experience with, or strong interest in, LLM/AI application development

- prompt design, tool/function calling, agent architectures

- Understanding of GA4 and Google Analytics Data/Admin APIs , or a fast ability to pick up new analytics platforms
- A pragmatic, product-minded approach to engineering - comfortable making sensible early-stage tradeoffs (buy vs. build, "positive enough" vs. gold-plated) rather than over-engineering
- Strong data governance instincts - you think about access control, PII, and auditability without being told to

Nice to have

- Familiarity with the Model Context Protocol (MCP) specifically
- Experience with reverse-ETL tools (Hightouch, Census) or CDP-style data activation
- Experience with Shopify's API/data model
- Exposure to CI/CD pipelines (GitHub Actions) and infrastructure-as-code (Terraform)
- Frontend experience (Next.js/React) for eventually building a client-facing dashboard

Why join You'll be building a genuinely new product from the ground up — not maintaining someone else's legacy system — with direct input into architecture decisions, a real (paying) client base to build for, and a technical roadmap that already spans infrastructure, data engineering, and applied AI. You'll work closely with our analytics and client delivery team, so what you build gets used immediately, not shelved.

To apply, please send your CV and a short note on relevant projects to [contact email] with the subject line "AI & Data Engineer — Digitxl".

📌 AI & Data Engineer (India)
🏢 DigitXL
📍 India