HGS - Senior Consultant - Data Platform

Position Summary:

As a Senior Consultant, you will lead the architecture and delivery of enterprise-grade data platforms on Google Cloud. You aren't just building pipelines; you are designing scalable, secure, and cost-effective ecosystems. You will act as a bridge between technical teams and business stakeholders, ensuring that data architectures align with long-term strategic goals.

Key Responsibilities:

- Architectural: Hands on knowledge of end-to-end ELT/ETL architectures using Medallion (Bronze/Silver/Gold) or Data Mesh patterns in BigQuery.

- Advanced Pipeline Engineering: Build complex, event-driven, and streaming pipelines using Dataflow (Apache Beam) and Pub/Sub. Hands on experience in automating data pipelines using workflows or Airflow

- Data Ops & CI/CD: Own the deployment lifecycle. Implement infrastructure-as-code using Terraform and automate SQL transformations using Dataform or dbt.

- Performance & Cost Governance: Conduct deep-dive audits of BigQuery usage.

- Security & Compliance: Design row-level and column-level security models. Implement data masking and PII discovery using Cloud DLP and Dataplex.

- Mentorship: Mentor 2 to 4 consultants, performing code reviews and providing technical guidance on complex "blocking" issues.

- Mange and implement Data governance framework, Role based access control on BQ tables, Data lifecycle, Data lineage, Security and compliance.

Education: Bachelor's degree in a relevant field;

Experience and Requirements:

- Experience: 5 to 8 years in Data Engineering, with at least 3+ years dedicated to GCP.

- Engine Mastery: Deep expertise in BigQuery (Internal mechanics, query plans, search/vector indexes).

- Programming: Advanced Python (Pandas, PySpark, Beam SDK) and Expert-level SQL.

- Orchestration: Experience building complex, dynamic DAGs in Cloud Composer (Airflow).

- Certification: Google Cloud Associate Data Practitioner or Professional Data Engineer.

- Tools: Familiarity with version control (Git) and CI/CD pipelines building for automated code deployments.