Lead Business Data Analyst at Discover
Discover. A brighter future.
With Discover, you’ll have the chance to make a difference at one of the world’s leading digital banking and payments companies. From Day 1, you’ll do meaningful work you’re passionate about, with the support and resources you need for success. We value what makes each employee unique and provide a collaborative, team-based culture that gives everyone an opportunity to shine. Be the reason millions of people find a brighter financial future, while building the future you want, here at Discover.
Discover Financial Services is seeking Lead Business Data Analyst to join our Enterprise Data Quality team. Successful candidates will collaborate with both Business and Technology cross-functional teams to gather requirements, understand and design business process, working in agile framework to deliver value to business.
On top of that, as a Lead Business Data Analyst, you will provide analytics and engineering leadership to enable data quality management framework and leverage the best technology solution to drive high quality data culture at DFS. You will be on the cutting edge of finding and integrating new technology and tools for data centric projects. For your first initiative, you will focus on collaborating with business data owners to identify and implement meaningful DQ checks on critical data elements. You will also be helping build customized solution for automatic DQ checks across multiple platforms while coming up simplified processes for issue remediation.
The ideal candidate will be passionate about Discover Financial Services data insights and its mission of driving high quality data environments. A successful candidate will have understanding of data modeling practices and have basic analytical skills and be able to work in a dynamic, fast-changing business environment.
- Work with Business Data Stewards and Stewardship team to triage “logical” DQ rules, refine the verbiage to ensure meaningful DQ rules are implementable and collaborate with engineers for implementation and execution.
- Drive CDE (Critical Data Elements) business rules intake, implementation, assessment and escalation.
- Partner with DQ product owner and engineers to design and implement Data Quality check progress report and bring up visibility for DQ implementation.
- Lead the initiatives to develop and document DQ remediation process, and provide oversights for DQ remediation activities in SOR and SOT layer.
- Help promote a culture of clear documentation and partner with Corporate Risk Management and Governance team to create job aids, standard procedures related to data quality management area.
- DQ Standards & procedure development, maintenance and training
- Maintain DQ rule repository, develop and come up with creative ways to conduct training pertaining to DQ intake, implementation, execution, monitoring and remediation.
- Collaborate with PO and engineers to improve already existing processes through automation of manual work
- Perform necessary testing to ensure automated processes perform correctly
- Create road map for DQ rule migration activities
- Develop meaningful DQ KRI metrics and drive the normalization and remediation efforts to correct any known data quality gaps
- Partner with business and technology teams to develop data applications. Identify business data ingestion and processing frameworks. Coordinates and obtains data application requirements from the business. Translates business requirements to development teams. Assist with development and testing processes. Coordinate data application and model deployments and validations.
- Assists with the development of models, analytic processes, and reports. Provides guidance on the development of data consumption processes.
- Ensures data governance policies are followed by implementing and validating data lineage, quality checks, classification, etc.
- Provides support for deployed data applications and analytical models. Identifies data problems and guides issue resolutions.
- Provides data and technical consulting during data application design. Provide technical consulting on data composition and data engineering.
At a minimum, here’s what we need from you:
- Bachelors degree in Information Technology, or related field
- 4+ years of work experience in Data Analysis, Business Analysis, data application programming, ETL development, migrating to next generation database, or related
- In lieu of education experience, 6+ years of work experience in Data Analysis, Business Analysis, data application programming, ETL development, migrating to next generation database, or related
If we had our say, we’d also look for:
- Excellent written and verbal communication, presentation and professional speaking skills
- Prior experience with Banking or Financial domain is a plus
- Experience in SQL, AWS, and Tableau
- Proven background working in Teradata, Snowflake and big data environments
- Ab Initio DQE (Data Quality Environment) architecture
- Ab Initio Express IT business rule development
- A deep understanding of Enterprise Metadata Management and Data Quality Principal and how high quality data fuels safe and sound operations, and innovation
- Strong ability to build and leverage external relationships
- Decision making abilities while gathering information and then put your decisions into action
- Creative and independent thinker with the ability to understand and translate complex problems and business processes into practical system requirements and solutions
- Ability to provide guidance and clear instructions to engineering teams to achieve objectives
What are you waiting for? Apply today!
The same way we treat our employees is how we treat all applicants – with respect. Discover Financial Services is an equal opportunity employer (EEO is the law). We thrive on diversity & inclusion. You will be treated fairly throughout our recruiting process and without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status in consideration for a career at Discover.