Join Deloitte's Technology & Transformation practice as an experienced GCP Data Engineer – Senior Consultant. This role is pivotal in designing, developing, and optimizing scalable cloud-based data solutions on Google Cloud Platform (GCP). You will collaborate with cross-functional teams to construct modern data pipelines, data lakes, and analytics platforms, directly contributing to enterprise digital transformation initiatives.

Deloitte's expertise lies in unlocking value from vast datasets. Our global network offers strategic guidance and implementation services, enabling companies to manage data from diverse sources and transform it into accurate, actionable insights. We focus on business intelligence, data management, performance management, and advanced analytics technologies, including big data, cloud, cognitive, and machine learning.

Key responsibilities include designing and developing scalable ETL/ELT pipelines using GCP services such as BigQuery, Dataproc, Pub/Sub, Composer (Airflow), Dataflow, and Cloud Storage. You will build and maintain cloud-native data architectures, develop batch and real-time data processing solutions, and implement robust data models, quality checks, and governance frameworks.

Further duties involve optimizing SQL queries and pipeline performance for large-scale datasets, collaborating effectively with business stakeholders, architects, and analytics teams. You will also be instrumental in migrating on-premises data platforms to GCP cloud environments, ensuring the security, scalability, monitoring, and reliability of data platforms. Support for CI/CD implementation and DevOps practices, along with mentoring junior developers and participating in code reviews, is also expected.

The ideal candidate possesses 5–8 years of overall IT experience, with a minimum of 3+ years focused on GCP Data Engineering projects. Essential skills include strong hands-on expertise with Google Cloud Platform (GCP) services like BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer/Airflow, alongside strong SQL and Python programming abilities.

Preferred qualifications include experience with Spark, Hadoop, or distributed data processing frameworks, and a solid understanding of ETL/ELT tools and data warehousing concepts. Familiarity with Git, CI/CD pipelines, Agile methodologies, data governance and security best practices, and tools like Terraform or Infrastructure as Code is beneficial. Exposure to Kubernetes/Docker and knowledge of BI tools such as Tableau, Power BI, or Looker are also advantageous. A B.Tech/BE in Computer Science or Information Technology is required, with GCP certifications being a plus.