Join Deloitte's Technology & Transformation practice as a GCP Data Engineer. You will be instrumental in guiding clients through their data journey, unlocking the value within vast datasets. Our team offers strategic advice and implementation services, transforming raw data into actionable insights for informed decision-making and a competitive edge. We focus on business intelligence, data management, performance management, and advanced analytics including big data, cloud, and machine learning technologies.

This role involves managing client relationships and ensuring the successful delivery of projects. As the primary liaison between Deloitte and its clients, you'll ensure alignment on goals, timelines, budgets, and desired outcomes, driving client satisfaction and business expansion.

Design and implement scalable ETL/ELT pipelines on Google Cloud Platform (GCP). Develop cloud-native data architectures leveraging GCP services. Create robust data models, implement quality checks, and establish governance frameworks. Optimize SQL queries and enhance pipeline performance for efficiency. Support on-premise to cloud data migration initiatives, ensuring platform scalability, monitoring, and reliability.

Collaborate closely with architects, analysts, and business stakeholders. Actively participate in agile delivery processes and sprint execution. Contribute to solution design and implementation. Support the adoption of CI/CD and DevOps practices within data engineering workflows.

We are seeking candidates with 5-8 years of overall IT experience, including a minimum of 3+ years specifically in GCP Data Engineering projects. Prior experience in consulting or large-scale enterprise environments is essential.

Technical proficiency required includes strong hands-on experience with Google Cloud Platform (GCP) and expertise in BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer (Airflow). You must possess strong programming skills in Python and SQL. Familiarity with Spark, Hadoop, or other distributed data processing frameworks, ETL/ELT concepts, and data warehousing principles is also necessary. Experience with batch and real-time data processing is expected.

Additional desirable skills include familiarity with Git and version control systems, CI/CD pipelines, and Agile development methodologies. A solid understanding of data governance and data security best practices is important. We also value experience with Terraform or Infrastructure as Code, exposure to Kubernetes and Docker, and knowledge of BI tools like Tableau, Power BI, or Looker. GCP certifications such as Professional Data Engineer or Associate Cloud Engineer are a plus.