GCP Tech lead
Job Description
Description
Summary
We are seeking a Senior Data Engineer with a distinguished background in Google Cloud Platform (GCP) to spearhead the evolution of our enterprise data ecosystem. With 5–8 years of professional experience, the successful candidate will operate as a technical authority, designing and deploying sophisticated data architectures that bridge the gap between complex raw data and strategic business intelligence. This role demands a mastery of distributed computing, advanced Python development, and expert-level SQL optimization to ensure the integrity, scalability, and cost-efficiency of our global data assets.
Core Responsibilities
Scalable Data Modeling: Lead the development of high-performance data models (Star, Snowflake, Data Vault) optimized for multi-petabyte scale and high-concurrency analytics.
Hybrid & Multi-Cloud Strategy: Provide technical leadership on data integration strategies spanning GCP, on-premise systems, and third-party SaaS environments.
Software Engineering Excellence: Develop reusable Python libraries and frameworks to standardize data ingestion, logging, and error-handling across the engineering team.
Infrastructure as Code (IaC): Drive operational maturity by managing cloud resources exclusively through Terraform, ensuring robust versioning and environment parity.
Security & Compliance: Architect data security protocols including VPC Service Controls, IAM Least Privilege, and data masking/encryption to meet global compliance standards (GDPR, SOC2).
Observability: Establish comprehensive monitoring and alerting frameworks for data health, ensuring high availability and meeting stringent Service Level Objectives (SLOs).
Stakeholder Alignment: Act as a primary technical liaison between Data Science, Business Intelligence, and Executive leadership to translate business goals into technical roadmaps.
Summary
We are seeking a Senior Data Engineer with a distinguished background in Google Cloud Platform (GCP) to spearhead the evolution of our enterprise data ecosystem. With 5–8 years of professional experience, the successful candidate will operate as a technical authority, designing and deploying sophisticated data architectures that bridge the gap between complex raw data and strategic business intelligence. This role demands a mastery of distributed computing, advanced Python development, and expert-level SQL optimization to ensure the integrity, scalability, and cost-efficiency of our global data assets.
Core Responsibilities
- Architectural Strategy & System Design
Scalable Data Modeling: Lead the development of high-performance data models (Star, Snowflake, Data Vault) optimized for multi-petabyte scale and high-concurrency analytics.
Hybrid & Multi-Cloud Strategy: Provide technical leadership on data integration strategies spanning GCP, on-premise systems, and third-party SaaS environments.
- Advanced Engineering & Pipeline Automation
Software Engineering Excellence: Develop reusable Python libraries and frameworks to standardize data ingestion, logging, and error-handling across the engineering team.
Infrastructure as Code (IaC): Drive operational maturity by managing cloud resources exclusively through Terraform, ensuring robust versioning and environment parity.
- Data Governance, Security & Performance
Security & Compliance: Architect data security protocols including VPC Service Controls, IAM Least Privilege, and data masking/encryption to meet global compliance standards (GDPR, SOC2).
Observability: Establish comprehensive monitoring and alerting frameworks for data health, ensuring high availability and meeting stringent Service Level Objectives (SLOs).
- Technical Leadership & Collaboration
Stakeholder Alignment: Act as a primary technical liaison between Data Science, Business Intelligence, and Executive leadership to translate business goals into technical roadmaps.
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