Data Analytics Engineer

BankUnited, Inc.•Miami Lakes, FL

About The Position

The Data Analytics 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 Analytics 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 business units across the organization 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). The Data Analytics Engineer works closely with a multifunctional team of data engineers, data analysts, and AI/ML solutions engineers. As a result, this individual is exposed to bleeding-edge generative AI technology and the latest large language models and will have a hand in helping develop full-stack applications that leverage those technologies.

Requirements

Bachelor's Degree in Computer Science, Data Analytics, Data Science, Management Information Systems or a related field
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
Required hands-on experience with Snowflake, including data modeling, performance optimization, and building and maintaining production data pipelines
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

Nice To Haves

Preferred experience with dbt (data build tool) for data transformation, testing, and analytics workflow orchestration

Responsibilities

Creates and maintains optimal data pipeline architecture
Assembles large, complex data sets that meet functional / non-functional business requirements.
Identifies, designs, and implements internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Works 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
Combines raw information from different sources to create consistent and machine-readable formats
Develops and tests architectures that enable data extraction and transformation for predictive or prescriptive modeling
Supports the data mining, reporting and general analytics needs of the department
Identifies process gaps and recommend new opportunities for process improvement through the use of quantitative analytics
Applies statistical techniques to interpret risk and develop solutions for business consumption
Leverages 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
Performs 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.