Senior BI Lead :

Data & Analytics :

- Role Type: Full-time Consultant

- Work Mode: Remote

- Working Hours: 2:00 PM 10:00 PM IST

About the Role :

We are building a modern data platform on AWS to unify operational data across the enterprise. The Senior BI Backend Engineer sits at the center of our BI team, responsible for transforming clean, validated Silver-layer data into the Gold layer a Redshift star schema that powers Tableau dashboards and business reporting across the company.

Silver data is delivered by a dedicated Data Integration team, so your focus is squarely on modeling: designing and building dbt models that produce reliable, performant, well-governed Gold tables. This is a hands-on senior individual contributor role. You bring deep dbt and SQL expertise, a strong instinct for data modeling, and the judgment to make the right call when requirements are ambiguous. You will work closely with the BI Backend Lead, Tableau developers, and business stakeholders to ensure Gold data is accurate, timely, and easy to consume.

What You'll Do :

Gold Layer Modeling (dbt) :

- Design and build dbt models that materialize clients Gold-layer star schema in Amazon Redshift fact tables (chassis events, service records, customer interactions) and dimensions (chassis, customer, location, date, service) from Silver source data.

- Own model architecture decisions: staging vs. intermediate vs. mart layers, incremental vs. full-refresh strategies, grain definitions, and fan-out/fan-in patterns.

- Implement SCD Type 2 dimension handling for slowly changing entities (chassis, customer) using dbt snapshots or equivalent patterns.

- Write and maintain a comprehensive dbt test suite uniqueness, not-null, referential integrity, accepted values, and custom business-rule tests to ensure Gold data quality before it reaches consumers.

- Manage schema evolution thoughtfully: version breaking changes, communicate impacts to Tableau developers upstream, and maintain backward compatibility where feasible.

Redshift Performance & Governance :

- Design distribution and sort keys tuned to client's primary query patterns (filter by chassis ID, date range, region) to deliver sub-second p95 query response for operational dashboards.

- Analyze query plans, identify bottlenecks, and tune WLM and materialization strategies as dashboard usage and data volumes grow.

- Maintain and evolve AWS Lake Formation access policies column- and row-level filtering for BI analysts, business users, data science, and operations teams ensuring the right people see the right data.

- Configure and manage Redshift Datashares to expose Gold tables to downstream consumers.

Data Quality & Governance :

- Own data quality at the Gold layer: design the test strategy, monitor test results, and work with the Data Integration team when upstream Silver data issues affect Gold.

- Maintain Gold asset registration and column-level lineage in OpenMetadata, ensuring analysts can discover, trust, and understand the data they consume.

- Collaborate with data owners to map Gold columns to governed business terms in the OpenMetadata business glossary.

Collaboration & Standards :

- Define and enforce dbt coding standards, model naming conventions, and documentation practices that make the Gold layer maintainable as the team and model count grow.

- Partner with Tableau developers to understand dashboard requirements and design Gold models that serve them efficiently acting as the translation layer between raw data and business-ready reporting.

- Work with the BI Backend Lead to break down requirements into sprint-level tasks and deliver against Phase 1 and Phase 2 platform milestones.

- Document model logic, grain definitions, and known data limitations in dbt docs and Confluence so consumers can self-serve answers to common questions.

What You'll Bring :

Required :

- 10+ years of overall experience and 5+ years of data engineering or analytics engineering experience, with the majority focused on data modeling and transformation in a production environment.

- Experienced in mentoring / leading the team of resources.

- Expert-level dbt you have owned a dbt project end to end, including model architecture, testing strategy, incremental models, snapshots, macros, and documentation.

- Advanced SQL you write complex queries fluently and understand how a columnar warehouse like Redshift executes them; you have tuned slow queries and know where to look first.

- Hands-on experience with Amazon Redshift, including distribution keys, sort keys, and query plan analysis.

- Strong data modeling fundamentals star schema design, fact and dimension table patterns, SCD Type 2, grain definition, and fanout awareness.

- Experience with AWS data governance tooling: Lake Formation, IAM, and Glue Data Catalog.

- A track record of owning data quality not just running tests someone else designed, but building the testing framework and knowing what to test and why.

Nice to Have:

- Familiarity with Apache Iceberg or another open table format as a Silver-layer source.

- Experience with OpenMetadata, DataHub, Atlan, or a similar data catalog/lineage platform.

- Basic Python for dbt macros, pre/post hooks, or ad hoc data validation scripting.

- Exposure to Tableau or other BI tools enough to understand what downstream consumers need.

- Prior experience in a technical lead or senior IC capacity setting standards, reviewing others' models, and influencing how a team works.

Our Stack:

You'll be working with the following technologies from day one:

- Transformation: dbt (Silver to Gold modeling)

- Warehouse: Amazon Redshift ra3 (Gold layer)

- Silver Source: S3 + Apache Iceberg (delivered by Data Integration)

- Governance: AWS Lake Formation, Glue Data Catalog, Redshift Datashares

- Catalog & Lineage: OpenMetadata

- Observability: OpenMetadata, CloudWatch, Redshift Audit Logs

- BI Downstream: Tableau (consumed via Redshift Datashares)