Senior Data Engineer - Data & Analytics

SUMMARY:

The Data Engineer will play a critical role in designing, implementing, and maintaining the bank's enterprise data platform. This individual will develop scalable, reliable, and high-performance data pipelines, ensure data quality and integrity, and drive Data Engineering initiatives across the organization. They will collaborate closely with stakeholders across the Enterprise Data & Analytics (ED&A) team to support, manage, and advance our enterprise data initiatives.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Business Engagement & Impact

Collaborates with ED&A Team to ensure alignment with enterprise data architecture standards.

Participates in cross-functional initiatives to ensure data availability and consistency across the enterprise.

Ensures data lineage and metadata are documented and maintained.

Technical Execution

Designs, develops and maintains Snowflake database structures.

Designs, develops, and maintains ETL/ELT pipelines using Informatica, SQL, and Python.

Builds and maintains data models for reporting and analytics.

Platform & Strategy Alignment

Designs, develops and maintains Snowflake database structures.

Designs, develops, and maintains ETL/ELT pipelines using Informatica, SQL, and Python.

Builds and maintains data models for reporting and analytics.

Collaboration & Enablement

Partners with business analysts and finance, operations, and risk teams to understand data requirements and translate them into technical solutions.

Provides guidance to downstream teams on data consumption best practices.

Works with compliance teams to ensure regulatory and security requirements are met.

Mentors junior team members and provide knowledge sharing to elevate team capabilities.

Ethics & Responsible AI

Identifies opportunities to improve ETL processes, performance, and data quality.

Remains current with emerging data engineering technologies, tools, and best practices.

Drives awareness of responsible data use within business teams.

OTHER REQUIREMENTS:

Banking is a highly regulated industry and you will be expected to acquire and maintain a proficiency in the Bank's policies and procedures, and adhere to all laws, rules and regulations that are applicable to your conduct and the work you will be performing. You will also be expected to complete all assigned compliance training in a timely manner.

Strong understanding of data modeling concepts (star schema, snowflake schema, SCD2) and best practices.

Strong understanding of data partitioning, indexing, and performance optimization.

Familiarity with data governance and compliance frameworks.

Proficiency in Microsoft Office Products including Excel, PowerPoint and Word.

Strong analytical, problem-solving, and debugging skills.

Excellent communication skills, with the ability to translate business requirements into technical solutions.

Strong attention to detail and commitment to data quality.

Ability to manage multiple priorities in a fast-paced environment.

Collaborative mindset with the ability to work across teams.

Proactive problem solver with a focus on scalable and maintainable solutions.

Bachelor's degree and minimum of 5 years of experience in data engineering, ETL development, and analytics-focused roles required or equivalent combination of education and experience. Degree in computer science, Information Systems, or related field, preferred.

Minimum of 3 years' experience with Informatica, Snowflake, DBT, SQL and Python Programming, required.

Experience with API-based data ingestion and streaming platforms preferred.

Experience in financial services or banking data environments, preferred.