Data Engineer

About the role

The Technical Engineering Lead will be responsible for leading and working alongside a team of seasoned engineers to maintain all aspects of the system health and ensure the on-time, quality delivery of software releases. This role focuses on providing operational intelligence and insights, and positioning Schwab as a data-driven organization using a world-class Data Exchange (DX) platform.

Responsibilities

• Provide technical and project leadership to data pipeline development.
• Understand the needs of the business and align on a solution to drive delivery.
• Drive Agile development supporting organizational priorities and innovation.
• Collaborate with analysts and other stakeholders to understand data requirements and deliver tailored solutions.
• Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
• Develop robust ETL processes to integrate data from diverse sources into our data ecosystem.
• Implement data validation and quality checks to ensure accuracy and consistency.
• Mentor junior team members to ensure team and project success.
• Implement data security controls and access management policies to protect sensitive information.
• Drive outcomes and team performance and collaborate with all to achieve results.
• Work closely with development, product owner, and team members to decompose stories, design features, and prioritize tasks.
• Navigate cross-functional communication to ensure alignment between teams and within one team.
• Create and maintain artifacts for production support and deployment processes and ensure smooth handoff to support teams.
• Identify technology risks and dependencies early to establish mitigation plans.
• Meet periodically with onshore and offshore developers and application support to review and improve processes.
• Demonstrate ability to disagree, debate with data, and commit to deliver regardless of the outcome.

Requirements

• Expertise in ETL development, Data Quality, Best Practices, Exception Handling.
• SQL, Google Cloud Products including BigQuery, Cloud Storage, Dataflow, Composer, Pub/Sub, SQL Server Integration Services.
• Expertise in Informatica (IDMC/IICS) and Python coding skills.
• Used AI in development lifecycle to gain efficiency.
• Business Analysis experience to perform data analysis to translate business requirements to data mapping.
• Exceptional track record in delivering results and business outcomes.
• Experience in maturing teams at different levels.
• Masters or bachelor’s degree in computer science, Information Technology or similar/equivalent area of study.
• Minimum of 3 years working in the financial services industry.
• Minimum of 8 years of solid data engineering experience.
• Minimum of 2 years project lead experience in matrixed organization.
• Strong understanding of Data Warehouse concepts (star schema, slowly changing dimensions, fact/dimension modeling) and Operational Data Exchanges/Stores.
• Solid understanding of data lifecycle, metadata management, and governance standards.
• Strong communication and stakeholder management skills across technical and non-technical audiences.
• Willingness to learn new skills and keep up with technology changes in future to meet business needs.
• Prior experience working in an onshore/offshore model driving development outcomes.

Preferred

• Experience working with and sourcing data from Corporate Systems like Workday, BMC Remedy Helix, Jira, Rally, etc.
• Experience providing guidance, direction, and feedback to other technical staff to meet agreed upon objectives.
• Ability to analyze, propose, and implement timely, effective, quality solutions for all issues or problems within area of responsibility.
• Excellent verbal and written communication skills required for composing and delivering technical presentations or other forms of documentation to various levels of technical and non-technical management.
• Proficient managing multiple priorities in a well-organized, dynamic, geographically dispersed environment.
• Strong understanding of Data pipelines and patterns.
• Experience in dev tools such as GitHub, Bamboo, Liquibase.