Data Engineer- Consumer/Small Business

SUMMARY: The Data Engineer will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company's data architecture to support our next generation of products and data initiatives. This individual will also be responsible for supporting Consumer/Small Business units through the utilization of technical and business knowledge to recommend solutions that solve business problems and reporting needs, amongst other skill sets. This includes identifying and defining data analytics needs as well as the structuring and analysis of data from multiple source systems for the purposes of creating and maintaining reporting (e.g. visual and flowchart modeling).

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following. Other duties and special projects may be assigned.

• Create and maintain optimal data pipeline architecture
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Work closely with IT departments to build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies
• Combine raw information from different sources to create consistent and machine-readable formats
• Develop and test architectures that enable data extraction and transformation for predictive or prescriptive modeling
• Support the data mining, reporting and general analytics needs of the department
• Identify process gaps and recommend new opportunities for process improvement through the use of quantitative analytics
• Apply statistical techniques to interpret risk and develop solutions for business consumption
• Leverage understanding of multiple data structures and sources to perform complex data manipulation using advanced data extraction and analytical tools and techniques
• Recognizes the connection between the business operations and analytics to influence business strategies through the interpretation and explanation of data to stakeholders
• Supports development of innovative approaches and best practices
• Perform any other assignments as directed by manager.
• Adheres to and complies with applicable, federal and state laws, regulations and guidance, including those related to anti-money laundering (i.e. Bank Secrecy Act, US PATRIOT Act, etc.).
• Adheres to Bank policies and procedures and completes required training.
• Identifies and reports suspicious activity.
  
  

EDUCATION

Bachelor's Degree in Computer Science, Data Analytics, Data Science, Management Information Systems or a related field

Experience

• At least 4 years working with data modeling, software implementation, enhanced reporting analytics and/or related experience in financial services data analysis and/or application development
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Mastery of analytic and data visualization tools such as SAS, SQL, Adobe Analytics Tableau, Google Analytics, Python or R, AWS Cloud Services (Cloudwatch ,EC2, EMR, Redshift, Athena,Glue) etc
• Ability to multitask, meet deadlines, manage competing demands/multiple projects, maintain a strong sense of urgency and follow through in addressing issues
• Effective and persuasive presentations (verbal and written) for project teams and business leaders
• Maintains strong attention to detail in high-pressure situations
• Solid understanding of data warehouse and dimensional modeling concepts