Google Cloud Platform Lead Data Engineer (W2 Only)

Role Overview

We are seeking a Senior Data Engineer with a distinguished background in Google Cloud Platform (Google Cloud Platform) to spearhead the evolution of our enterprise data ecosystem.

With 8-10 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
• Enterprise Framework Design: Conceptualize and implement end-to-end data architectures utilizing Google Cloud Platform s Modern Data Stack (BigQuery, Dataflow, Pub/Sub).
• 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 Google Cloud Platform, on-premise systems, and third-party SaaS environments.
• Advanced Engineering & Pipeline Automation
• Distributed Processing: Engineer highly resilient, low-latency streaming and batch pipelines using Apache Beam (Dataflow) and Cloud Composer (Airflow).
• 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
• System Optimization: Conduct deep-dive performance tuning of BigQuery environments, implementing partitioning, clustering, and slot management to optimize ROI.
• 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
• Strategic Mentorship: Serve as a mentor to mid-level and junior engineers, conducting rigorous code reviews and promoting best practices in DataOps.
• Stakeholder Alignment: Act as a primary technical liaison between Data Science, Business Intelligence, and Executive leadership to translate business goals into technical roadmaps.

Education

Bachelors or Masters in Information Technology, Computer Science or relevant field