GCP Data Engineer Lead

About this role

Key Responsibilities

• Lead and mentor the data engineering team for project delivery and technical excellence.

• Design and implement scalable ETL/ELT data pipelines on GCP.

• Build and optimize data lakes and data warehouses using BigQuery.

• Develop batch and real-time data processing solutions.

• Collaborate with architects, business stakeholders, analysts, and development teams.

• Perform code reviews and enforce engineering best practices.

• Support CI/CD implementation and DevOps best practices.

• Provide technical guidance during project planning and estimation.

Technical Skills

• Strong hands-on experience with Google Cloud Platform (GCP)

• Expertise in:

• BigQuery

• Git

• Cloud Composer

• Dataflow

• Pub/Sub knowledge

• Cloud Storage (GCS)

• Cloud Functions

• Looker knowledge

• Knowledge of BI/reporting tools such as Looker

• Strong experience Big query and SQL

• Good understanding of data modeling and warehousing concepts

• Experience with ETL/ELT frameworks and orchestration tools

• Knowledge of Terraform or Infrastructure as Code (IaC)

• Knowledge with CI/CD pipelines and Git-based workflows

• Familiarity with Airflow and DevOps practices

Leadership Skills

• Experience leading technical teams and client communication

• Strong problem-solving and decision-making abilities

• Ability to manage delivery timelines and technical risks

• Excellent communication and stakeholder management skills

Bachelor's or Master’s degree in Computer Science, Information Technology, Engineering, or a highly quantitative field.
Experience: 7-8 Years hands-on experience in data engineering, data warehousing, or large-scale software development.
All your information will be kept confidential according to EEO guidelines.
Sutherland is seeking an experienced and highly skilled GCP Data Engineer Lead to design, develop, and manage scalable cloud-based data solutions on Google Cloud Platform (GCP). The candidate will lead the data engineering team, drive architecture decisions, and ensure best practices in data pipeline development, data warehousing, and cloud-native solutions.
The ideal candidate should possess strong technical expertise in GCP services, modern data engineering practices, and team leadership capabilities.
Originally posted on Himalayas