GCP Data Engineer

Job Summary We are looking for 2 experienced GCP-focused Data Engineer / Platform Engineers with strong engineering depth and hands-on experience building scalable data platforms. The role requires expertise in designing and implementing end-to-end data pipelines and control frameworks, with the ability to derive actionable insights from data.

Core Responsibilities

• Design, build, and scale data platforms and pipelines on GCP, leveraging services such as BigQuery and related ecosystem tools
• Own and contribute to end-to-end development lifecycle—from requirements to production deployment and optimization
• Develop robust, scalable workflows for data ingestion, transformation, and processing
• Implement and optimize data models, pipelines, and transformations using Python (Pandas, PySpark) and SQL
• Build and operationalize analytical datasets to support reporting and downstream use cases
• Establish and enhance data control frameworks using a mix of enterprise tools and custom solutions
• Collaborate with cross-functional teams (business, risk, operations, technology) to translate requirements into scalable solutions
• Ensure data quality, validation, and performance optimization across pipelines and workflows
• Support production-grade reporting and dashboards (Tableau / Power BI) and enable data-driven decision-making

Must-Have Skills

• Deep expertise in GCP (architecture, services, and scalable system design)
• Strong software engineering and development experience across data platforms
• Proven experience building large-scale data pipelines and distributed systems
• Strong programming skills in Python (PySpark, Pandas) and SQL
• Experience with BigQuery and GCP-native data services
• Solid understanding of data modeling, optimization, and ETL/ELT frameworks
• Hands-on experience working across the full development lifecycle (design to deployment)

Good-to-Have Skills

• Ability to derive analytical insights and support business decision-making
• Experience with GenAI implementations or AI-driven workflows
• Exposure to data governance and control frameworks
• Experience integrating external data sources via APIs
• Familiarity with web scraping