Description

You will design, build, and optimize enterprise-scale data pipelines on Google Cloud Platform (GCP) within a hybrid big data architecture. You own the full lifecycle of data ingestion, transformation, governance, and curation, ensuring performance, cost efficiency, and strict compliance with security standards.

Responsibilities

• Re-write and enhance existing data pipelines to meet evolving business needs and enterprise architecture standards.
• Design and build production-grade data pipelines from ingestion to consumption using Java, Python, GCP Dataflow, and Apache Airflow.
• Implement Collibra workflows using Java and integrate KMS/HSM solutions with GCP data services for security and compliance.
• Optimize data pipelines for performance, scalability, and cost efficiency across large-scale data lakes.
• Partner with external consultants and managed services teams to deliver compliant solutions and communicate technical concepts to non-technical stakeholders.

Required Skills

• 8+ years of engineering experience in Big Data, Data Analytics, and Data Integration.
• 2+ years of hands-on experience in GCP Data Engineering and Cloud Analytics solutions.
• 5+ years of programming experience with Python and Java, including Spring Boot, Spring MVC, and REST API development.
• Hands-on experience with CI/CD pipelines using Concourse or Jenkins.
• Experience designing and optimizing data models using BigQuery.
• Proficiency with GCP Data Ingestion technologies: Dataflow, Fusion, and Airflow.
• Experience implementing metadata management solutions on GCP.
• Bachelor’s degree or equivalent work experience.

Key Skills

Education

Any Graduate