Role Summary :

We are seeking a skilled BigQuery Developer / Cloud Data Analyst to design, develop and maintain MIS' and reports using GoogleSQL (BigQuery) programming to ensure data is stable, reliable and performant. The ideal candidate must have deep expertise in ANSI-SQL / GoogleSQL, strong experience with complex data transformations, and a solid understanding of data modelling principles in a cloud-based analytics environment. The role directly supports our production retail lending workflows and machine learning foundations via the GCP Vertex AI platform.

Roles & Responsibilities :

- Database Design and Development : Designing and creating BigQuery table schemas, optimized views, and Materialized Views. This includes defining informational primary/foreign keys and establishing robust upstream data validation rules to maintain data integrity.

- Query Optimization : Writing and optimizing complex GoogleSQL (BigQuery) queries for efficient data retrieval, transformation, and downstream performance improvement. This involves deeply analyzing BigQuery Execution Plans and slot utilization metrics to actively eliminate performance bottlenecks.

- Performance and Maintenance : Monitoring runtime query performance, troubleshooting production datasets, and implementing targeted schema optimization for optimal cost and processing efficiency. This involves configuring and managing Table Snapshots, Table Clones, Time-Travel windows, and securing partitioned/clustered data assets.

- Adhoc Reporting & Ticketing : Working on and promptly closing Service Tickets raised by operational business stakeholders via tracking platforms like JIRA or ServiceDesk. Successfully furnishing accurate, high-quality Management Information Systems (MIS), reports, or required features in the precise layout requested by stakeholders.

- Collaboration and Documentation : Working closely with functional business units, engineering teams, and machine learning groups to ensure seamless pipeline integration. Maintaining highly disciplined documentation of procedures, underlying code modifications, schemas, and historical ticket closures for future retrieval.

Technical Skillset :

- SQL Proficiency : Professional-level expertise in GoogleSQL (BigQuery) programming. Absolute mastery over complex analytic queries, window functions, user-defined functions (UDFs), scripting blocks, and struct/array multi-table operations.

- Database Design Principles : Comprehensive knowledge of cloud-native data modelling, schema denormalization, structural partitioning, and storage clustering best practices tailored for column-oriented cloud data warehouses.

- Tools & Techniques : Ability to interpret query execution logs and cloud billing metrics for system optimization. Practical proficiency with operational ticketing ecosystems (JIRA / ServiceDesk) and cloud-centric version control (Git / GitLab / GitHub).

- Cloud Ecosystem : Strong operational knowledge of core Google Cloud Platform database and ML-adjacent services, emphasizing BigQuery administration, Cloud Storage (GCS), and integration interfaces for Vertex AI feature discovery.

- Problem-Solving & Teamwork : Strong analytical, critical thinking, and diagnostic skills to handle unstructured data requests under strict business timelines while collaborating smoothly in cross-functional squads.

Qualification & Experience :

- Education : Bachelor's degree from a reputed institution or university in Data Modelling, Analytics, Computer Science, Information Systems, or a closely related technical field.

- Experience : 3 to 7 years of active database development or cloud analytics experience, featuring a dedicated focus on Google Cloud Platform infrastructure.

- Candidates must show demonstrated proof-of-work involving : Practical deployment of GCP-BigQuery's Data Partitioning and Clustering techniques; Advanced algorithmic query optimization reducing cloud slot footprints and storage-scan costs; Clear understanding of data governance, Identity & Access Management (IAM), and row/column-level security controls in GCP; Experience provisioning clean datasets to feed analytics suites (Looker, Tableau) or AI infrastructure (Vertex AI pipelines).