Job Description:

*Other locations in EC footprint to be considered

Enterprise Credit is an integrated underwriting, monitoring and product management division servicing Business Banking, Global Commercial Banking, Commercial Real Estate, Global Corporate & Investment Banking (GCIB), Global Markets and Global Wealth & Investment Management. It interfaces with an aligned, fulfillment and servicing function, supported by an independent risk management approval organization. With employees located in nearly 300 cities around the world, the business is focused on streamlining the delivery of credit to improve client experience and enhance productivity.

The Enterprise Credit Analytics and Transformation Strategy (ECATS) organization is responsible for aggregating and delivering high-quality global banking data for enterprise use. The team uses advanced analytics and our data to drive credit revenue growth, reduce expenses and risk, and increase client value. In addition, ECATS drives portfolio optimization and pricing strategy, develops business intelligence reporting to provide relevant and timely information to the credit organization, and leads efforts across Global Banking to ensure compliance with enterprise data-related standards and initiatives.

The EC Data Engineering / Credit Sync / SWAT team is part of ECATS responsible for providing data solutions for a variety of business driven use cases and includes data analysis, system design, root cause analysis, reporting and analytics, etc.

The candidate will be responsible for understanding business information needs, translating those needs into specific data sources and elements, leveraging our tools and resources to build automated solutions that connect and consolidate the required data sources, and sustaining those processes through robust governance controls. The role will require the development of deep understanding of information repositories and the business context of the information they contain as well as the technical skills to build repeatable, robust processes to connect and consolidate information sources. The role will also require the candidate to think deeply about how processes are sustained through lightweight but effective governance and controls and how those controls are evidenced. A key focus will be on researching data incidents, understanding the data flows and consumption processes affected by the incident, analyzing data to identify discrepancies and root causes, documenting and communicating the incident cause and business impact and working with Technology partners to implement long-term strategic solutions.

As the Senior Data Engineer you will:

• Establish an integrated Data Strategy to support multiple information product workstreams with data capture, consolidation and analytical capabilities

• Align development teams to execute on our data strategy and deliver capabilities to support and sustain business information product needs

• Ensure that data governance and controls are built as part of the solution and can be sustained

• Bring order to disparate requirements with high tolerance for ambiguity, very strong problem solving ability, and excellent client engagement skills

• Pivot quickly as business needs evolve, always keeping the ultimate project objective in mind. Manage evolving project requirements while continuously learning quickly on-the-job

• Ensure compliance with enterprise standards around product management, information security, data access, data governance and model risk management

• Synthesize analytical findings for consumption by senior business executives

• Develop preliminary hypotheses rapidly, focusing on the most important insights to meet the business need

• Be a story teller capable of delivering practical data insights in a compelling manner actionable by senior leadership

• Demonstrate intellectual curiosity for solving difficult business problems

Required Skills:

• Undergraduate or advanced degree in analytical field (e.g., Computer Science, Economics, Mathematics, Statistics, Engineering, Operations Research, Physics), data bootcamp certification, or industry experience in analytical roles (e.g., consulting, modeling, data engineering, data analysis) or equivalent work experience

• Ability to work in large and medium sized project teams, as self-directed contributor with a proven track record of being detail orientated, innovative, creative, and strategic

• Influencer with great interpersonal skills and proven ability to achieve alignment across a range of different views and interests

• Excellent communicator able to convey complex information in an understandable, compelling, and persuasive manner to senior executives

• Strong aptitude for technical concepts and ideas

• Thought leader in data science and analytics who can define analytical agenda for projects, demonstrates ability to frame ambiguous business questions into analytical plans (e.g., assessing data needs, sourcing files, preparing data, creating new features, evaluating quality, etc.), and executes with precision

• Demonstrated experience in Data Management and/or Data Governance preferred planning and establishing a sustainable control environment around data-driven processes

• Demonstrates highly proficient skills in each of the following areas: quantitative, analytics, and technical skills

• Travel up to 10% of time.

Desired Skills:

• Knowledge of modern data mining, quantitative research, and data science techniques (e.g., decision trees, regressions, machine learning, string similarity, behavioral analytics, look-a-like models)

• Understanding of Agile software development and operating model and understanding of Product Owner’s role within the Agile framework

• Financial services background preferred, as is broad understanding of Commercial systems and information repositories

• Experience working with or managing solutions in Tableau, Alteryx, Trifacta, Python, or similar tools a plus

Shift:

Hours Per Week: