Overview

Job Title: Senior Data Engineer Google Cloud Platform

Responsibilities

• Lead Cloud Transformation: Drive the migration of data pipelines and workloads from on-premises environments to Google Cloud Platform, ensuring minimal disruption and maximum efficiency.
• Design Cloud-Native Data Solutions: Architect and implement secure, scalable, and resilient data solutions on GCP using key services like BigQuery, Dataflow, Cloud Storage, Cloud Composer, and Pub/Sub.
• Build & Modernize Data Pipelines: Develop, optimize, and support robust ELT/ETL workflows for data ingestion, transformation, and integration across diverse enterprise systems.
• Drive Innovation and Adaptability: Champion the adoption of modern data engineering practices and adapt quickly to new technologies and changing business requirements to continuously improve our data ecosystem.
• Ensure Data Quality & Governance: Implement data validation, lineage tracking, monitoring, and robust security controls within the GCP environment to maintain data integrity and compliance.
• Collaborate and Communicate: Partner directly with business stakeholders to gather requirements, present cloud solutions, and provide clear updates to leadership on migration progress and technical strategy.
• Optimize for Performance and Cost: Tune data pipelines and system configurations for optimal performance and cost-effectiveness in a large-scale cloud environment.
• Enable Advanced Analytics: Build foundational data models and services that empower Data Scientists, BI Analysts, and other consumers to access and leverage data at scale.
• Knowledge Sharing & Mentorship: Mentor junior engineers, promote best practices in cloud data engineering, and foster a culture of continuous learning and collaboration.

Qualifications

• Bachelors or masters degree in computer science, Engineering, or a related field.
• 5-6 years of experience in data engineering, with a strong focus on cloud platforms.
• Proven hands-on experience designing and building data solutions on Google Cloud Platform (GCP).
• Demonstrated experience with large-scale data migration projects from on-premises systems to the cloud.
• Strong proficiency in GCP data services (e.g., BigQuery, Dataflow, Cloud Storage, Cloud Composer).
• Expertise in modern ETL/ELT design, data warehousing principles, and large-scale data integration.
• Proficiency with SQL and programming languages such as Python.
• Familiarity with Infrastructure as Code (IaC) principles and tools like Terraform.
• Excellent communication skills, with the ability to engage with both technical and non-technical stakeholders.
• A proactive and adaptable mindset, with strong analytical and problem-solving abilities.
• Exposure to hybrid-cloud environments and tools like Ab Initio, Azure Data Factory, or Databricks.
• Familiarity with BI and reporting tools like Power BI or Looker.

Nice to have

• Google Cloud Professional Data Engineer Certification.