Role Overview :

As a GCP Data Engineer, you will be at the forefront of architecting and managing scalable data pipelines that drive critical business intelligence and machine learning initiatives. You will work closely with cross-functional teams, including data scientists, product managers, and software engineers, to transform raw data into actionable insights. By designing robust data architectures and optimizing cloud-native storage solutions, you will directly influence the efficiency of our data ecosystem, ensuring that stakeholders across the organization have reliable, real-time access to the information needed to make high-impact strategic decisions.

Key Responsibilities :

- Design and implement end-to-end data pipelines using Google Cloud Platform services to ensure seamless data ingestion, transformation, and delivery for internal business units.

- Optimize BigQuery performance and storage costs to provide cost-effective and high-speed analytical capabilities for the data science and analytics teams.

- Collaborate with engineering leads to automate data workflows using Cloud Composer and Airflow, reducing manual intervention and improving overall system reliability.

- Maintain data integrity and security standards across all cloud environments to ensure compliance and protect sensitive organizational information.

- Troubleshoot and resolve complex data bottlenecks to support the continuous availability of mission-critical dashboards and reporting tools used by leadership.

Required Skillset :

- Demonstrated expertise in building scalable data solutions on GCP, specifically utilizing BigQuery, Dataflow, Pub/Sub, and Cloud Storage.

- Strong proficiency in Python or Java for data processing, coupled with advanced SQL skills for complex data modeling and query optimization.

- Proven ability to communicate technical data concepts to non-technical stakeholders, ensuring alignment between engineering outputs and business requirements.

- A proactive mindset toward problem-solving, with the ability to adapt to a hybrid work environment in Bengaluru while collaborating with global teams.

- A Bachelor's degree in Computer Science, Information Technology, or a related quantitative field, supported by a track record of delivering high-quality data engineering projects within a 3 to 8-year career span.