Job Description

Required Technical Skills

·         Advanced SQL and complex query writing.

·         Strong experience with Google Cloud Platform (GCP) and BigQuery.

·         Strong dbt Cloud and dbt Core expertise.

·         Dimensional data modeling and data mart design experience.

·         Data lineage, root cause analysis, and data flow troubleshooting.

·         Configuration management, Git, branching strategies, merging, conflict resolution, and rebasing.

·         CI/CD pipeline implementation and deployment automation.

·         Data quality monitoring, testing frameworks, and governance controls.

·         Knowledge of PII handling, data privacy, and security standards.

Responsibilities

·         Build and Maintain High‑Quality Data Models.

o   Design and implement scalable business-layer models, marts, and OBTs used by the organization.

o   Choose correct modelling techniques (dimensional, OBT, etc.) based on business needs.

o   Ensure models serve as a reliable single source of truth.

·         Own End‑to‑End Development Lifecycle.

o   Translate business requirements into technical solutions.

o   Develop, test, document, and deploy data models through CI/CD.

o   Follow software‑engineering standards for analytics code.

·         Ensure Coding Standards and Best Practices.

o   Apply and enforce coding standards for SQL and DBT cloud.

o   Conduct quality code reviews focusing on logic, consistency, and documentation.

o   Produce clean, well-structured, maintainable code.

·         Data Quality, PII Handling & Testing.

o   Add generic and custom tests to ensure accuracy of transformed data.

o   Handle PII safely (masking, hashing, access‑control).

o   Treat data quality issues as critical defects, not afterthoughts.

·         Diagnose and Resolve Data Issues:

o   Investigate discrepancies across source → transformation → BI layers.

o   Debug failures and pipeline breaks using compiled SQL and lineage.

o   Work independently until issues are resolved.

·         Improve and Optimize the Codebase:

o   Identify refactoring opportunities for older or inefficient models.

o   Optimize query performance and cost using Big Query tools.