Big Data Engineer

Role Summary The Data Engineer is responsible for designing, developing, testing, and supporting the Data Foundation platform's data pipelines, data products, and data services. This role works closely with the Data Engineering Lead, Architecture Team, Service Owner, Platform Engineering Lead, and business stakeholders to deliver trusted, scalable, and maintainable data solutions that enable analytics, AI, integrations, and operational reporting. The ideal candidate is a hands-on engineer with strong experience in data integration, SQL, Python, cloud-native data platforms, and modern engineering practices. They are passionate about building reliable data solutions, improving data quality, and enabling enterprise-scale data consumption. Key Responsibilities Data Pipeline Development • Design, develop, and maintain batch and event-driven data pipelines. • Build and enhance reusable data ingestion, transformation, and publishing services. • Implement data movement patterns supporting source systems, APIs, file-based integrations, and streaming platforms. • Develop scalable and efficient solutions that meet performance, reliability, and maintainability requirements. • Support enterprise data products, canonical data models, and shared data assets. Data Engineering & Integration • Develop data transformations using SQL, Python, and modern data engineering frameworks. • Build integrations with internal applications, third-party platforms, and cloud services. • Develop and support APIs that expose data products and services to consumers. • Contribute to master data management and data standardization initiatives. • Participate in design discussions and provide engineering input on solution decisions. Data Quality & Reliability