Analytics Engineer

Fi Money is a new age money management app designed to simplify your financial life. With Fi, you can save, pay, invest, or borrow, all in one place. You can track and analyze your expenses across Fi and all your other bank accounts. You can also apply for a credit card, access instant loans, and grow your wealth and more with our range of investment options.

We are seeking a hands-on Analytics Engineering & Automation Lead who can both execute and lead a small team of analysts/engineers. The role will design and scale datamarts, dashboards, business rules, and ML deployment pipelines. They will also own process automation, SLAs, and governance to ensure a reliable, future-ready analytics ecosystem.

Key Responsibilities

1. Analytical Engineering

-Architect and oversee datamarts and curated data views across domains.

-Establish data modeling best practices, documentation, and governance.

-Mentor team members on SQL and data engineering patterns.

2. Dashboarding & Visualisation

-Drive dashboard standards, governance, and usability across business teams.

-Lead the design of executive-level and operational dashboards.

-Manage a backlog of dashboard requests with clear SLAs.

3. Business Rule Engines (BREs)

-Own the design and governance of production rule engines for credit/fraud policies.

-Ensure scalable, tested, and version-controlled deployment of rules.

-Partner with Risk/Policy/Product teams for agile implementation.

4. ML Deployment & Maintenance

-Lead the deployment and monitoring of batch-based ML models.

-Define standards for model execution, monitoring, and retraining workflows.

-Collaborate with model builders for smooth model-to-production handoff.

5. Automation & SLAs

-Define and enforce SLAs for data, dashboard, and BRE changes.

-Introduce automated solutions using tools like GenAI, n8n, dbt, CI/CD.

-Continuously improve efficiency of analytics delivery.

6. Team Leadership

-Lead a small team (2–4 analysts/engineers) with responsibility for prioritization, quality, and development.

-Conduct regular reviews, mentorship, and skill development.

-Act as the bridge between business stakeholders and the analytics team.

Qualifications

-5–8 years of experience in analytics engineering / BI / data platforms.

-Advanced SQL, data modeling, and pipeline orchestration experience.

-Strong BI expertise (Tableau, PowerBI, Looker, or equivalent).

-Hands-on with ML model deployment (batch pipelines, monitoring, scheduling).

-Familiarity with cloud platforms (BigQuery, Snowflake, GCP/AWS/Azure).

-Experience with workflow automation (Airflow, dbt, n8n, CI/CD).

-Prior experience in leading small teams and stakeholder management.

This is a 5 days work from office role and we are in Brookfield, Bengaluru.