Lead the data engineering team to support, maintain, and enhance PDS data products and ETL pipelines.
Responsibilities
Support, maintain, and enhance PDS data products, ETL pipelines built using DBT, AWS Glue, Databricks, and other cloud‑native technologies.
Analyze, troubleshoot, and resolve production incidents, ensuring high availability, reliability, and adherence to SLAs.
Develop pipeline enhancements, bug fixes, and operational automation to improve platform performance, scalability, and operational efficiency.
Ensure data quality, integrity, and operational stability through validation, monitoring, root cause analysis, and proactive issue resolution.
Collaborate with Analytics Engineering, Cloud Engineering, and Business teams to support feature releases, production deployments, and continuous improvements.
Lead internal technical authority overseeing data architecture projects for external partners, ensuring alignment with enterprise standards and strategic goals.
Compensation
The pay range for this position is $80.00 - $87.00/hr.
Responsibilities
Provide expert oversight for data projects delivered by external partners
Review partner-created architecture, code, and technical designs
Participate in meetings with implementation partners and internal stakeholders
Monitor progress and ensure adherence to operational principles
Identify and flag deviations, risks, or quality concerns
Looking for an experienced Senior Product Engineer to join the Risk & Control Governance team to build governance, assurance, and data foundations that ensure risk decisions are consistent, explainable, auditable, and continuously monitored.
Responsibilities
Building and maintaining data ownership, lineage, and quality monitoring systems
Designing continuous monitoring and validation systems to verify controls
Implementing end-to-end audit trails, change history tracking, and explainability tooling
Integrating with Risk API team to embed governance and assurance capabilities
Designing robust, high-throughput solutions for large volumes of data
Lead and provide technical leadership for multiple data‑engineering teams supporting the Wealth domain, driving architecture, design, and end‑to‑end data pipeline delivery.
Compensation
$168,550 - $191,850
Responsibilities
Lead four data‑engineering teams supporting the Wealth domain
Provide hands‑on technical leadership across architecture, solution design, implementation, and engineering quality
Review technical designs and code, challenge engineering decisions constructively
Guide the development and operation of end‑to‑end data pipelines with a focus on Databricks
Establish and reinforce engineering standards for data quality, error handling, monitoring, and reliable pipeline development
Requirements
Bachelor’s or master’s degree in Computer Science, Engineering, Information Technology, or a related field of study.
Nice to have: Direct experience with Databricks and Spark
Nice to have: Experience leading globally distributed or offshore engineering teams
Nice to have: Experience establishing engineering standards across multiple teams or domains
Nice to have: Experience within financial services, retirement, wealth management, or investment‑related data environments
Build and operate connectivity, profiling, and graph/search foundation for enterprise ontology and knowledge management platforms.
Compensation
The annual salary for this position is anticipated to be between $100,000 and $120,000 USD, depending on experience, qualifications, geographic location, and other factors permitted by law.
Responsibilities
Transform raw operational and master data sources into clean, lineage-tracked, governed, and queryable knowledge assets
Design and support data connectivity, metadata management, graph platforms, ingestion frameworks, and search capabilities
Build adapters and integration frameworks for BigQuery, Cloud SQL, REST APIs, Apigee, GCS, Pub/Sub
Establish scalable ingestion patterns for operational, transactional, and master data systems
Support API-based integrations across enterprise applications and data platforms
Requirements
Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related discipline
Lead the development of a data governance and data quality foundation across multiple Business Units within Apple’s Places organization, enabling broader AI transformation strategy.
Responsibilities
Shape future of data-driven decision making across Apple’s Places portfolio
Lead initiatives to ensure data is trusted, well-governed, and fit for purpose at scale
Enable high-quality insights that power strategic planning, operational excellence, and long-term portfolio decisions
Translate complex technical data and AI architectures into clear business outcomes for leadership
Requirements
Degree or Certification in Business Analytics, Data Science, or an equivalent data discipline
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