Join a leading Technology & Transformation practice focused on unlocking the full potential of data. This role offers the opportunity to guide companies in managing data effectively and transforming it into actionable insights for informed decision-making. The practice specializes in business intelligence, data management, performance management, and advanced analytics, including big data, cloud, and machine learning technologies.

As a GCP Data Engineer Consultant, you will be instrumental in designing, developing, and supporting robust data engineering solutions on Google Cloud Platform. This position demands close collaboration with business stakeholders, architects, and delivery teams to build scalable data pipelines, optimize workflows, and ensure successful project outcomes. Strong cloud data engineering expertise, hands-on development experience, and a collaborative consulting approach are essential for success in this dynamic environment.

Key responsibilities include designing, developing, and maintaining scalable ETL/ELT pipelines on GCP, building data ingestion and transformation solutions using core GCP services, and supporting the migration of data workloads from on-premises or legacy systems to GCP. You will implement data quality validation and monitoring mechanisms, create detailed technical documentation, and troubleshoot pipeline failures and performance bottlenecks. The role also involves supporting the implementation of secure and scalable cloud data architectures, collaborating closely with stakeholders to gather requirements, and actively participating in agile ceremonies and delivery activities.

We are seeking candidates with 3-5 years of overall IT experience, including a minimum of 2 years of hands-on experience in GCP Data Engineering projects. Essential technical skills encompass strong proficiency in Python and SQL, with experience in developing efficient data processing frameworks and optimizing SQL queries. You should have experience building ETL/ELT pipelines using cloud-native services, possess knowledge of batch and streaming data processing, and understand data warehousing and dimensional modeling concepts. Familiarity with Spark and distributed data processing frameworks is also expected. Experience with Git-based source control, CI/CD tools, and Agile/Scrum methodologies is required. A basic understanding of data governance principles and best practices for data quality, security, and access management is necessary. A B.Tech/BE or equivalent degree is preferred.