Senior Analytics Engineer

Superset; Bengaluru; On-site; INR 4,200,000 - 6,500,000; Full time

Job summary

Superset is seeking a Senior Analytics Engineer to own how we turn raw operational data into trustworthy analytics. You will govern a versioned, tenancy‑safe dataset layer on Redshift, serving as the quality gate for dashboards drafted by an in‑house AI agent.

You’ll define standards, tests, and scale strategies for dashboards used by enterprise university and employer customers. You’ll work hands‑on on Redshift, dbt modeling, and ensure multi‑tenant security while collaborating with product,

Qualifications

• 5+ years in analytics engineering, data engineering, or BI, with deep SQL and strong data modeling (star schemas, wide tables, semantic layers).
• Hands‑on with a columnar data warehouse Redshift preferred; Snowflake or BigQuery is fine.
• dbt, or an equivalent modeling and testing discipline.
• Has owned a BI / dashboarding surface end‑to‑end (Superset, Looker, Metabase, Tableau, or an in‑house tool), and understands multi‑tenant row‑level security and why the same metric can drift between dashboards.
• Accountable for correctness you build tests and checks into your models, you don’t just ship queries.

Responsibilities

• Own the governed dataset layer. Design canonical, versioned, tenancy-safe datasets on Redshift starting as blessed base SQL definitions and growing into a dbt‑style modeled layer that every customer dashboard is built on.
• Set the standards. Define how we scope data per tenant, how we version datasets so a refresh never silently breaks a customer’s view, and how we test that the numbers are right.
• Be the quality gate. Review dashboards drafted by our in‑house AI agent, verify the numbers, and publish them (draft → published) to the right customer audience.
• Improve our standard dashboards. Raise the correctness, clarity, and performance of the dashboards every customer receives.
• Steer the pipeline. Partner with engineering and our data-pipeline consultant on the MySQL → DMS → Redshift → Airflow pipeline and help shape its architecture.
• Optimize for scale. Tune slow queries and stored procedures, and help evolve Redshift as our primary analytics backend.

Skills

Analytics engineering

Data modeling

SQL

BI/dashboarding

Testing & data quality

Tools

Redshift

dbt

Looker

Superset

Airflow

Python

Job description

Level: Senior individual contributor (not a people-manager role)

Role Overview

We’re looking for a Senior Analytics Engineer to own how Superset turns raw operational data into trustworthy analytics.

We deliver custom dashboards to enterprise university and employer customers, and our top priority is making those numbers consistent and easy to trust.

You’ll own the foundation that makes that possible: a governed, versioned dataset layer that every dashboard is built on and you’ll be the human quality gate over an in-house AI agent that drafts dashboards for you to review and publish.

This is a senior, hands-on IC role. You are the person who defines what “correct” means for our data and is accountable for it the standard our team and our AI tooling build against.

One great engineer here beats three average ones.

What You’ll Do

• Own the governed dataset layer. Design canonical, versioned, tenancy-safe datasets on Redshift starting as blessed “base” SQL definitions and growing into a dbt-style modeled layer that every customer dashboard is built on.
• Set the standards. Define how we scope data per tenant, how we version datasets so a refresh never silently breaks a customer’s view, and how we test that the numbers are right.
• Be the quality gate. Review dashboards drafted by our in-house AI agent, verify the numbers, and publish them (draft → published) to the right customer audience.
• Improve our standard dashboards. Raise the correctness, clarity, and performance of the dashboards every customer receives.
• Steer the pipeline. Partner with engineering and our data-pipeline consultant on the MySQL → DMS → Redshift → Airflow pipeline and help shape its architecture.
• Optimize for scale. Tune slow queries and stored procedures, and help evolve Redshift as our primary analytics backend.

What We’re Looking For

• 5+ years in analytics engineering, data engineering, or BI, with deep SQL and strong data modeling (star schemas, wide tables, semantic layers).
• Hands‑on with a columnar data warehouse Redshift preferred; Snowflake or BigQuery is fine.
• dbt, or an equivalent modeling and testing discipline.
• Has owned a BI / dashboarding surface end‑to‑end (Superset, Looker, Metabase, Tableau, or an in‑house tool), and understands multi‑tenant row‑level security and why the same metric can drift between dashboards.
• Accountable for correctness you build tests and checks into your models, you don’t just ship queries.

You’ll Thrive Here If You

• Set a standard rather than just completing tasks you think about scalability, versioning, and long‑term maintainability.
• Take ownership and follow through from design to production.
• Communicate clearly and collaborate across product, engineering, and customer‑facing teams.
• Are comfortable amplifying AI / agent tooling in your workflow we lean on it heavily and want someone who makes it better, not someone who fears it.
• Are curious, keep up with evolving tools, and challenge existing approaches when there’s a better way.

Nice to Have

• Apache Airflow or other workflow orchestration
• Python
• Experience with embedded or customer‑facing analytics
• Experience in a fast‑moving product company
• Docker, Git, and CI/CD

How Superset Helps You on Your Journey

Two things are well ingrained in our culture.

First, we need people to take ownership we don’t micromanage or follow up on our people because we trust them to deliver the best work possible.

Second, we make sure to provide resources and remove the bottlenecks that get in the way of that work.

• If you’re at a stage in life where you’re looking for challenges, you’re at the right place.
• We’re a team of proactive, versatile, independent, and collaborative mindsets, with the liberty to experiment and be creative wherever necessary.
• We understand that making mistakes comes in handy when you’re growing as long as you’re learning from them, you’ll fit well with us.
• Our customers rely on our products to do their most important work, which means they rely on us to build things the right way.