GCP Data Engineer Lead

Sutherland · via Himalayas ·

TypeFull-time job
LocationIndia
Posted2 hours ago
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
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