Role: Lead GCP Data Engineer/Looker
Hire: (Full-Time)
Job Summary
We are seeking a highly skilled and motivated Lead GCP Data Engineer to join our team on a full-time basis. In this role, you will lead the design, development, and optimization of scalable data platforms, robust data pipelines, and advanced analytical solutions on the Google Cloud Platform (GCP). You will collaborate closely with business stakeholders, data analysts, and engineering teams to translate analytical requirements into impactful, scalable data solutions.
Key Responsibilities
Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP).
Build and optimize enterprise data solutions using BigQuery, Cloud Storage, Dataflow, Dataproc, Cloud Composer, and Pub/Sub.
Develop and maintain semantic data models using LookML in Looker.
Create reusable dashboards, reports, and analytics solutions to support critical business decision-making.
Lead data architecture discussions and provide technical guidance and best practices to engineering teams.
Implement data governance, data quality standards, security policies, and performance optimization best practices.
Collaborate directly with business stakeholders to translate complex analytical requirements into scalable data architectures.
Mentor junior engineers, foster engineering excellence, and conduct rigorous code reviews.
Troubleshoot and resolve data pipeline, reporting, and performance bottlenecks.
Work closely with DevOps and cloud infrastructure teams to implement seamless CI/CD pipelines and infrastructure as code practices.
Required Skills & Expertise
1. GCP Data Engineering
Strong, hands-on enterprise experience with:
BigQuery
Cloud Composer (Airflow)
Dataflow
Dataproc
Cloud Storage
Pub/Sub
Cloud Functions
IAM & Security best practices
2. Looker / LookML
Advanced experience in Looker development and administration.
Expertise in LookML modeling, explores, views, dimensions, measures, and derived tables.
Experience designing, scaling, and maintaining enterprise semantic layers.
Strong understanding of dashboard development, caching strategies, and performance tuning.
3. Data Engineering Fundamentals
Advanced SQL writing and complex query optimization skills.
Extensive experience with ETL/ELT frameworks.
Deep data warehousing and dimensional modeling (Star/Snowflake schemas) expertise.
Hands-on experience with both batch and real-time data processing workflows.
4. Programming Languages
Python
SQL
Shell Scripting
Preferred Skills
Experience with dbt (data build tool).
Working knowledge of Terraform and Infrastructure as Code (IaC).
Experience with CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins.
Exposure to machine learning workloads and MLOps on GCP.
Familiarity with Agile/Scrum delivery methodologies.
Qualifications
Employment Type: Full-Time
Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related technical field.
Google Cloud Certifications:
Professional Data Engineer (Required)
Professional Cloud Architect (Preferred)
Nice-to-Have
Domain experience in Retail, Financial Services, Healthcare, or E-commerce.
Proven migration experience moving legacy on-premise systems or other cloud platforms (AWS/Azure) to GCP.
Strong stakeholder management and client-facing communication skills.