Data Engineer, WW Ops Finance - S&A
Are you passionate about building data platforms that empower thousands of users to discover, trust, and act on data? Do you thrive in fast-paced environments where you can design scalable systems, automate data workflows, and drive innovation through modern cloud technologies? If you enjoy solving complex data challenges and delivering solutions that have direct business impact, then the Worldwide Operations Finance Standardization & Automation (S&A) team has an exciting opportunity for you!
We are seeking a customer-centric Data Engineer to help build and scale our unified data management and discovery platform — enabling global Finance teams to find the right data faster, ensure data quality, and make confident, data-driven business decisions. You will work with one of the world's largest and most complex data environments, building solutions that serve thousands of customers across multiple domains.
As a Data Engineer in WW Ops S&A, you will design, implement, and maintain scalable data infrastructure, ETL pipelines, and platform services that power enterprise-scale data discovery and analytics. You will build solutions to integrate with multiple heterogeneous data sources, develop metadata management frameworks, and create self-service capabilities that accelerate time-to-insight. You should have strong technical skills in Python, SQL, and AWS services, along with excellent communication skills to collaborate with business owners, Finance teams, and engineering partners to translate requirements into reliable, scalable solutions.
Key job responsibilities
- Design, build, and maintain scalable data pipelines and ETL workflows using Python, SQL, and AWS services (S3, Glue, Redshift, Lambda, EMR, MWAA) to support enterprise-scale data platforms
- Develop and optimize data models, metadata management frameworks, and catalog systems that enable fast, reliable data discovery for thousands of internal customers
- Build and maintain microservices and APIs (API Gateway, Lambda) that power platform features including search, data ingestion, and cross-service integrations
- Implement data quality frameworks, monitoring, and alerting to ensure high data reliability, freshness, and compliance with governance standards
- Automate data onboarding workflows and self-service capabilities to reduce manual effort and accelerate time-to-insight for data consumers and producers
- Collaborate with cross-functional teams — including product managers, BI engineers, and business stakeholders — to translate business requirements into scalable technical solutions
- Participate in system design, code reviews, and operational excellence practices including incident response, root cause analysis, and continuous improvement
- Contribute to GenAI-powered features and AI-driven workflows that enhance the data discovery and analytics experience
About the team
We are part of the Worldwide Operations Finance Standardization & Automation (S&A) organization, building a unified data management and discovery platform serving global Finance teams. Our platform combines a dataset catalog, metric catalog, AI assistant, and interactive query experience enabling thousands of customers to find and act on data faster. We are rapidly scaling to support 10+ domains and data producer teams. Our tech stack includes AWS services (DataZone, OpenSearch, API Gateway, Lambda), microservices architecture, and modern frontend frameworks.
We are seeking a customer-centric Data Engineer to help build and scale our unified data management and discovery platform — enabling global Finance teams to find the right data faster, ensure data quality, and make confident, data-driven business decisions. You will work with one of the world's largest and most complex data environments, building solutions that serve thousands of customers across multiple domains.
As a Data Engineer in WW Ops S&A, you will design, implement, and maintain scalable data infrastructure, ETL pipelines, and platform services that power enterprise-scale data discovery and analytics. You will build solutions to integrate with multiple heterogeneous data sources, develop metadata management frameworks, and create self-service capabilities that accelerate time-to-insight. You should have strong technical skills in Python, SQL, and AWS services, along with excellent communication skills to collaborate with business owners, Finance teams, and engineering partners to translate requirements into reliable, scalable solutions.
Key job responsibilities
- Design, build, and maintain scalable data pipelines and ETL workflows using Python, SQL, and AWS services (S3, Glue, Redshift, Lambda, EMR, MWAA) to support enterprise-scale data platforms
- Develop and optimize data models, metadata management frameworks, and catalog systems that enable fast, reliable data discovery for thousands of internal customers
- Build and maintain microservices and APIs (API Gateway, Lambda) that power platform features including search, data ingestion, and cross-service integrations
- Implement data quality frameworks, monitoring, and alerting to ensure high data reliability, freshness, and compliance with governance standards
- Automate data onboarding workflows and self-service capabilities to reduce manual effort and accelerate time-to-insight for data consumers and producers
- Collaborate with cross-functional teams — including product managers, BI engineers, and business stakeholders — to translate business requirements into scalable technical solutions
- Participate in system design, code reviews, and operational excellence practices including incident response, root cause analysis, and continuous improvement
- Contribute to GenAI-powered features and AI-driven workflows that enhance the data discovery and analytics experience
About the team
We are part of the Worldwide Operations Finance Standardization & Automation (S&A) organization, building a unified data management and discovery platform serving global Finance teams. Our platform combines a dataset catalog, metric catalog, AI assistant, and interactive query experience enabling thousands of customers to find and act on data faster. We are rapidly scaling to support 10+ domains and data producer teams. Our tech stack includes AWS services (DataZone, OpenSearch, API Gateway, Lambda), microservices architecture, and modern frontend frameworks.