Data Engineer – GCP & Python

Position: Data Engineer Experience: 5+ years Locations: Huston, TX Or NYC, NY Notice Period: Immediate Joiners Work mode will be Hybrid - Candidate should be able to work from office, 5 days in a month. Job Overview We are seeking Data Engineers to join the Data Onboarding Engineering team. This role is focused on building and operating robust, scalable data pipelines that ingest and process 30+ TB of data daily, primarily using Python on Google Cloud Platform (GCP). The engineer will collaborate closely with business partners, researchers, and trading teams to onboard high-value datasets that directly power systematic trading and research workflows. The ideal candidate is highly hands-on, production-focused, and comfortable operating in a high-performance, data-intensive environment. Key Responsibilities • Work closely with business stakeholders to understand data requirements and usage patterns • Collaborate with engineers, researchers, and portfolio managers to onboard new and complex datasets • Design, build, and support production-grade ETL and data ingestion pipelines using Python • Operate and scale data pipelines running on Google Cloud infrastructure • Ensure strong standards around data quality, reliability, monitoring, and operational support • Handle large-scale batch data ingestion volumes (30TB+ per day) • Extend and enhance the existing data onboarding framework to support new data sources and formats • Troubleshoot and resolve pipeline failures and data quality issues in production • Contribute to documentation, operational runbooks, and engineering best practices Desired Skills and Experience Essential Skills • 3+ years of professional experience as a Data Engineer or in a similar role • 3+ years of hands-on experience building ETL pipelines in production environments • Strong Python programming skills for data processing and pipeline development • Practical experience with cloud-based data platforms, preferably Google Cloud Platform (GCP) • Solid understanding of data operations, including ingestion, processing, storage, quality, and lifecycle management • Strong SQL skills and familiarity with data modeling concepts Nice-to-Have Skills • Experience with Snowflake as a cloud data warehouse • Exposure to Spark or other distributed data processing frameworks • Familiarity with Lakehouse concepts (Delta Lake or similar formats) • Experience with event-driven or streaming data pipelines • Background working with financial, market, or alternative datasets • Knowledge of data observability, lineage, and governance tooling Behavioral Competencies • Strong problem-solving and analytical mindset • Excellent collaboration and communication skills • Ability to work effectively with cross-functional technical and non-technical teams • High ownership and accountability in a production environment • Comfortable working in a fast-paced, data-driven organization Educational Requirement: Bachelor’s or master’s in computer science.