Senior Analytics Engineer

About ACKO
ACKO is the protection destination for over 200 million tech-savvy families across India, protecting their families, assets and money. Launched in 2016, ACKO started by reimagining insurance, making it simple, hassle-free and customer-first. Today, our mission goes beyond that: we aim to touch the lives of 1 million users, building products that solve real-world problems with technology at the core.
We are not just another insurance company, our DNA is product-tech, and our approach is bold, innovative, and digital-first. From zero commission, zero paperwork, and instant renewals to same-day claims settlements and app-based tracking, ACKO is a Welcome Change from traditional insurers.
But what truly sets us apart Our people. At ACKO, every Ackers voice and ideas matter. Were a vibrant, inclusive team of creators, thinkers, and doers, building products that redefine protection while ensuring each Acker grows, thrives and does meaningful work.
Join us at ACKO, where bold ideas, real impact and tech-driven innovation redefine protection and peace of mind - and where YOU can make a real difference in peoples lives. ACKO is a product-tech company, launched in 2016, solving real-world problems for customers, starting with insurance. And as a customer-first organization serving the digitally-savvy, ACKOs value proposition of Welcome Change focuses on offerings that make insurance simple and hassle-free! With features such as zero commission, zero paperwork, instant renewal, same-day claim settlements, and app-based updates on claims, ACKO is a Welcome Change from traditional insurers.
Having said that, we are not just another conventional insurance firm, or the people consulted solely for claims! Anchored in a tech-centric philosophy, ACKOs approach fuels innovation, empowering us to develop comprehensive products that cater to every aspect of our customers insurance requirements. And while we are at it, we put our Ackers at the heart of everything we do. Were not your typical 9-to-5 workplace; were a vibrant and inclusive bunch of innovators and creators making sure every Ackers idea matters, their voice is heard, and their growth is part of our mission.
The problem youll solve
ACKOs data has grown as fast as the business, and it shows. We have tens of thousands of tables, fragmented metric definitions, and dashboards that dont always agree with each other. A single campaign analysis can spawn hundreds of redundant tables. Business teams spend time debating numbers instead of acting on them.
This is a greenfield consolidation effort with real stakes. Youll be hands-on building the clean, well-modelled data layer that analysts and business teams across policies, claims, marketing, and finance depend on every day.
Our data stack
Warehouse - Google BigQuery
Transformation - dbt Cloud (models, tests, macros, CI/CD)
Dashboarding - Tableau, PowerBI, Metabase
Orchestration - Apache Airflow
Data Quality - dbt tests + Soda core
Catalog / Lineage - OpenMetdata
Languages - SQL (primary), Python
What Youll Do
Youll work within the Analytics team alongside senior data Analysts. Your work will be measured by outcomes, not just tasks.

• Own data models end-to-end - write staging, intermediate, and mart-layer models for core domains (policies, claims, customers, marketing, finance) following dimensional modelling principles. Your models will be the single source of truth that analysts reference.
• Reduce the noise - audit existing tables and dashboards, identify redundant logic and fractured metric definitions, and consolidate them into clean, reusable models, so teams stop debating numbers and start using them.
• Make data trustworthy - define and implement tests and alerting so that broken data is caught before it reaches a dashboard. Own data health KPIs for your domains.
• Keep the warehouse lean - apply partitioning, clustering, and query best practices in BigQuery to keep performance high and costs predictable. Flag and fix inefficient patterns proactively.
• Be the partner analysts need — work directly with analysts in product, marketing, and finance, translate their reporting needs into well-structured models and migrate their dashboards (Tableau, PowerBI, Metabase) to the new layer.
• Maintain catalog hygiene — keep Data Catalog current — column-level descriptions, sensitivity tags, lineage — so the team spends less time asking where a table came from.
• Write docs people actually read — data dictionaries, model READMEs, onboarding guides. Good documentation is a multiplier for the whole team.
  

What Youll Need

• 4–8 years in analytics engineering, data engineering, or a data-heavy analyst role
• Strong hands-on dbt experience - models, tests, macros, sources, and CI/CD
• Advanced SQL - window functions, CTEs, performance tuning, query profiling
• Proficiency with Cloud Data warehouses like BigQuery, Snowflake, Redshift, or Databricks
• Solid understanding of dimensional modelling (star/snowflake schemas, grain, SCDs)

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• Experience building or migrating dashboards in Metabase, Tableau, PowerBI or Superset
• Working Python for data validation, transformation scripts, or pipeline support
• Ability to manage the data with agentic workflows to reduce manual effort and data discovery frictions
• Exposure to data quality frameworks like Great Expectations, Deequ, Soda Core or custom dbt tests
  

Good To Have
Experience with data catalog/metadata tools (OpenMetadata, DataHub, Amundsen, Alation), semantic/metric layers, or event-first modelling patterns.
Why youll love it here

• A problem worth solving
  

This isnt a maintenance role. The data mess is real, the greenfield opportunity is real, and the impact on 200M+ customer decisions is real. Youll be fixing something that matters.

• A direct path to architecture
  

Youll work alongside the Data Analysts who sets the standards. L3s influence design decisions.

• Fintech/insurtech domain depth
  

Policies, claims, risk, marketing, and finance - ACKOs data spans a uniquely complex, regulated, and fascinating domain. Youll develop expertise thats rare and valuable.

• Cross-functional visibility
  

Youll collaborate directly with product, marketing, and finance stakeholders - not just the data team. Your models drive decisions at the leadership level.