Lead GGP Engineer

Requirement/Must Have:

• Advanced hands-on experience with Google Cloud Platform (Google Cloud Platform).
• Strong expertise in BigQuery, Dataflow (Apache Beam), Pub/Sub, and Google Cloud Storage (GCS).
• Strong Python and SQL programming skills.
• Experience designing and implementing Medallion Architecture.
• Experience with cloud-based data pipeline architecture and development.
• Experience with QA frameworks for data pipelines such as Great Expectations, dbt tests, or equivalent.
• Strong understanding of data quality, reconciliation, and governance strategies.
• Agile delivery management experience including sprint planning and status reporting.
• Ability to lead technical teams and manage delivery execution.

Experience:

• Proven experience in Google Cloud Platform data engineering and cloud computing environments.
• Experience building batch and streaming data pipelines.
• Experience with data modeling, data architecture, and data management.
• Experience with QA strategy design and reusable testing frameworks.
• Experience leading offshore or distributed engineering teams.
• Experience with telecom data or high-volume telemetry data preferred.
• Advanced Google Cloud Platform certifications preferred.
• Experience with mentoring and knowledge transfer initiatives preferred.

Responsibilities:

• Lead pipeline architecture design for Netscout and Sandvine ingestion.
• Design source extraction, GCS landing, Dataflow transformations, and BigQuery loading across Bronze, Silver, and Gold layers.
• Design Medallion Architecture data flows and transition rules.
• Define data quality checks and validation strategies for each Medallion layer.
• Lead data reconciliation strategies and parity validation processes.
• Provide hands-on support for complex transformation logic and pipeline development.
• Define and manage end-to-end QA strategy, including test coverage, tooling, quality gates, and defect management.
• Architect reusable and parameterized test templates for batch and streaming pipelines.
• Review and validate pipeline and QA deliverables produced by engineering teams.
• Lead sprint planning, sprint reviews, and retrospectives using Agile methodologies.
• Maintain RAID logs and drive mitigation actions for risks and issues.
• Produce weekly status reports and maintain project delivery trackers.
• Coordinate with client Data Engineering teams regarding environments, access, and technical decisions.
• Manage task allocation and quality assurance for offshore engineers.
• Support knowledge transfer and mentoring activities.

Should Have:

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work in fast-paced cloud transformation environments.
• Strong leadership and collaboration skills.
• Experience working with enterprise-scale cloud data platforms.

Skills:

• Google Cloud Platform (Google Cloud Platform).
• BigQuery.
• Dataflow.
• Apache Beam.
• Pub/Sub.
• Google Cloud Storage (GCS).
• Python.
• SQL.
• Data Engineering.
• Data Architecture.
• Medallion Architecture.
• Data Quality.
• Data Reconciliation.
• Great Expectations.
• dbt.
• Agile Methodology.
• Sprint Planning.
• RAID Management.
• Data Modeling.
• Cloud Computing.
• Batch and Streaming Pipelines.
• Telecom Data Processing.

Qualification and Education:

• Bachelor s degree in Computer Science, Information Technology, Engineering, or related field preferred.
• Advanced Google Cloud Platform certifications preferred.
• Equivalent practical experience in cloud data engineering accepted.