Senior Data Engineer

The Senior Data Warehouse Data Engineer will develop, implement and maintain data platform solutions, ensuring optimal performance, reliability, and scalability for business and analytics teams. This role requires a strong background in data warehousing and data lakes, ETL processes, data pipelines, data governance, and collaboration, along with excellent problem-solving and analytical skills., * Data Warehouse Design and Development: Design, develop, and maintain data warehouse solutions that meet business requirements and support data-driven decision-making.

• ETL Process Implementation: Develop and manage ETL (Extract, Transform, Load) pipelines and processes to ensure accurate and timely data integration from various sources into the data warehouse.

• Data Modeling: Create and maintain logical and physical data models to support data warehouse solutions, ensuring data integrity, consistency, and accuracy.

• Performance Optimization: Monitor and optimize data warehouse performance, including query optimization, indexing, and partitioning strategies to ensure efficient data retrieval and processing.

• Data Quality Assurance: Implement and monitor data quality checks and validation processes to ensure adherence to defined SLA’s.

• Collaboration and Communication: Work closely with business stakeholders, data analysts, and other IT teams to understand data requirements, common pain points, evaluate their common needs, and finally turn them into internal warehouse tables or data services.

• Documentation and Reporting: Create and maintain comprehensive documentation of data warehouse architecture, processes, and procedures, and provide regular status reports to management.

• Collaborate with cross-functional teams to define and execute data strategies that leverage virtualization and fabric concepts to enhance data agility and support evolving business needs.

• Work directly with our Analytics and Data Science teams to define requirements and troubleshoot technical data issues in the Data Platform or Data Mappings/Pipelines.

• Design and implement data virtualization solutions to provide seamless data access and integration across diverse data sources. Ensure that data is easily accessible, governed, and secure, while enabling real-time data processing and analytics.

• Operational Support: Participate in on-call support rotation.

Other

• Adheres to all company policies, procedures, and business ethics codes.

• Completes required regulatory training as assigned.

• Maintains strict adherence to and compliance with all laws, rules, regulations, and internal controls specific to the role, including but not limited to Bank Secrecy Act, Anti-Money Laundering, USA Patriot Act, OFAC and Fair Lending regulations.

• Experience building data products for use by AI/ML

• Knowledge of data modeling techniques and tools (e.g., ERwin, Toad Data Modeler).

• Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.

• Attention to detail and a commitment to data quality and accuracy.

• Ability to manage multiple priorities and work in a fast-paced, agile, dynamic environment.

Core Competencies

• Demonstrating Member Obsession

• Puts themselves in the Member’s shoes

• Looks for friction points

• Makes it personalized and easy

• Demonstrating Performance Excellence

• Sets standards for elevating excellence

• Ensures elevated quality

• Takes responsibility

• Conducts continuous improvement

• Demonstrating Innovation

• Challenges current thinking

• Approaches change with a positive mindset

Experience

• Bachelor’s degree in Computer Science, Information Technology, or a related field or equivalent years of experience.

• Minimum of 5-7 years of experience in data warehousing, database management, or a related role.

• Minimum of 2-3 years of hands-on experience using Databricks.

• Strong proficiency in SQL and experience with database management systems (e.g., Oracle, SQL Server, MySQL, PostgreSQL).

• 5-7 years of hands-on experience with ETL tools and processes (e.g., Informatica, Talend, SSIS, Azure Data Factory).

• 5-7 years of hands-on experience with data warehousing concepts and best practices, and dimensional modeling.

• Experience with data integration from various sources, including structured and unstructured data, batch, and real-time.

• Experience building business and reporting views in a semantic layer.

• Must be bondable

Preferred Requirements

• Experience in the financial services or credit union industry.

• Experience building data products for use by AI/ML.

• Proficiency in programming languages such as Python, C#.

The Senior Data Warehouse Data Engineer is an exempt position and reports to the Manager, Data Warehouse and will be a part of the Enterprise Data Platform team at UFCU.

About UFCU

Our Credit Union was founded in 1936 and has grown to serve members throughout Texas and beyond. At UFCU, we are more than just a financial institution, and our people are more than just employees. We are dedicated to our purpose of empowering our Members to achieve financial success and build brighter futures.

In pursuit of our aspiration that UFCU is loved by millions of Members and built to thrive for generations, we are guided by our values:

• Purposefully Member-Obsessed: We are driven by a profound sense of empathy to deeply understand our Members’ needs and preferences, what brighter futures means to them, and the obstacles in their way. We act in our Members’ best interests, forever seeking to empower their financial success.

• Possibilities Reimagined: We are inspired to courageously experiment, learn, and iterate in pursuit of positive impact for our Members, UFCU, and coworkers. We challenge assumptions, embrace diverse perspectives, and make use of data and insights.

• Performance Excellence Rooted in Unwavering Integrity: We do the right thing, always. We champion teamwork, accountability, continuous improvement, and celebrate successful outcomes of others, fostering an inclusive environment of excellence and collaboration.