This position plays a key technical role within the Organizational Data Management department, responsible for creating and maintaining robust data architectures. The role emphasizes building dimensional star schema models, developing reliable ETL/ELT workflows, and supporting enterprise analytics through scalable, well-documented data solutions. It also involves collaboration across teams to ensure alignment with business needs and governance standards.
Responsibilities
- Design and manage comprehensive data models at conceptual, logical, and physical levels, with a focus on dimensional modeling using star schemas.
- Define and standardize fact tables and conformed dimensions, ensuring proper grain, key structures, and modeling consistency.
- Create reusable data frameworks to promote uniformity across certified data assets.
- Ensure data architecture meets current reporting demands while supporting future expansion, including integration of new data sources.
- Evolve data models and architectural patterns in compliance with enterprise standards.
- Develop and maintain ETL/ELT pipelines that consolidate data from core systems into analytical platforms.
- Act as secondary support for critical data pipelines, ensuring operational continuity and shared ownership.
- Monitor, tune, and resolve issues in data pipelines and databases to maintain performance, reliability, and data integrity.
- Troubleshoot production data issues related to availability, quality, and system performance.
- Implement data validation, reconciliation, and quality controls for certified data assets.
- Collaborate with BI and analytics teams to confirm data requirements and align with business definitions.
- Support audit, risk, and compliance initiatives by maintaining traceable, repeatable, and well-documented data processes.
- Work with the Data Governance team to apply data standards, definitions, and certification rules in technical implementations.
- Ensure data structures comply with enterprise policies on naming, classification, and domain alignment.
- Enable data lineage and metadata capture through thoughtful architectural design, without direct management of governance tools.
- Translate business and reporting needs into scalable technical data solutions in partnership with analytics and business units.
- Participate in Agile processes, including backlog refinement, design reviews, and iterative development.
- Clearly communicate architectural decisions, assumptions, and trade-offs to both technical and non-technical audiences.
- Adhere to established data engineering and architecture standards, patterns, and best practices.
- Use Git and GitHub for version control, code collaboration, and peer review.
- Maintain thorough technical documentation for data models, pipelines, and design decisions.
- Comply with BSA regulations and internal/external compliance policies.
- Demonstrate CARES Principles through daily interactions: building meaningful connections, showing intentional curiosity, and proactively solving problems.
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or a related discipline.
- Minimum of five years of professional experience in data architecture and data engineering.
- Experience working with enterprise data platforms in regulated or data-sensitive environments.
- Strong SQL skills and experience with relational databases such as Oracle or SQL Server.
- Proven experience designing data models for analytics and reporting purposes.
- Hands-on experience applying dimensional modeling techniques, including facts, dimensions, and star schemas.
- Experience building and maintaining ETL/ELT pipelines.
- Experience with data warehousing and analytical data architectures.
- Familiarity with cloud data platforms such as AWS or Azure.
- Strong analytical, problem-solving, and communication abilities.
- Proficiency with version control systems, especially Git and GitHub.
- Experience with code review and collaborative development workflows.
- Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
- Ability to produce clear documentation, analyses, and presentations that bridge technical and business contexts.
- Ability to interpret technical, business, and regulatory documents and generate accurate reports and procedures.
- Ability to build trust with technical and business partners through professionalism and clear communication.
- Ability to engage and influence stakeholders to align technical solutions with business goals.
- Ability to operate standard office equipment including computers, phones, printers, and projectors.
- Ability to lift up to 25 pounds.
Nice to Have
- Experience in a community bank or credit union setting.
- Master’s degree in a relevant field.
- Familiarity with modern cloud data warehouses such as Snowflake.
- Experience supporting analytics or data science teams.
- Knowledge of financial industry data and regulatory requirements.
- Experience with data modeling tools like ERwin or ER/Studio.
- Understanding of machine learning concepts and associated data needs.
- Experience with branching strategies such as Git Flow or GitHub Flow in data engineering contexts.
- Ability to mentor team members on version control best practices and GitHub efficiency.
- Familiarity with financial institution accounting, finance terminology, and business processes.
Tech Stack
SQL, Oracle, SQL Server, ETL/ELT, data warehousing, AWS, Azure, Snowflake, Git, GitHub, ERwin, ER/Studio, dimensional modeling, star schema, data governance tools
Team
Part of the Organizational Data Management (ODM) department
Additional Information
- The role emphasizes implementing dimensional star schema models and may involve supporting cloud data warehouse modernization efforts.
- The position requires adherence to CARES Principles: Connect (build meaningful relationships), Ask (be intentionally curious), and Resolve (actively seek solutions).
