RTR Title :- Programmer/Analyst: II (Intermediate)
Overview:
Our Enterprise Data Engineering department is growing, and we're looking for an outstanding Senior Data Engineer to join our team. The Senior Data Engineer will play a pivotal role in building and operationalizing the minimally inclusive data necessary for the enterprise data and analytics initiatives following industry standard practices and tools. Our goal is to be the Best performing Regional Bank in America, and we need data and analytics to meet that goal.
As a Senior Data Engineer, you will play a pivotal role in building and operationalizing the minimally inclusive data necessary for the enterprise data and analytics initiatives following industry standard practices and tools. Data Engineers will also test for data quality to ensure Huntington's data conforms to business rules and is accurate, complete, consistent, and uniform. The Data Engineer primarily focuses on building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for key data and analytics consumers like business/data analysts, data scientists or any persona that needs curated data for data and analytics use cases across the enterprise.
Responsibilities:
Architecting, creating and maintaining data pipelines
Assist with renovating the data management infrastructure to drive automation in data integration and management
Work in partnership with data science teams and with business analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements
Train counterparts across the organization in data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases
Work with data governance teams and participate in vetting and promoting content created in the business and by data scientists to the curated data catalog for governed reuse
Demonstrated ability to communicate complex results to technical and non-technical audiences
Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines
Strategic, intellectually curious thinker with focus on outcomes
Professional image with the ability to form relationships across functions Skills:
Strong experience with various Data Management architectures and processes
Strong ability to design, build and manage data pipelines for data
Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets
Demonstrated success in working with large, heterogeneous datasets to extract business value
Strong experience in working with DevOps capabilities like version control, automated builds, testing and release management capabilities
Demonstrated ability to communicate complex results to technical and non-technical audiences
Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines
Strategic, intellectually curious thinker with focus on outcomes
Professional image with the ability to form relationships across functions
Willingness and ability to learn new technologies on the job Experience:
4+ years of related experience in data management disciplines including data integration, modeling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks
4+ years of experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative, experience with data preparation tools and database programming languages
Strong experience with advanced analytics tools
Hands on data testing experience
Strong experience with data engineering tooling (e.g., Glue, Landa, Athena, AWS)
Strong knowledge of BI software tools
Strong experience with open-source and commercial data science platforms
Learn and/or Agile methodology
• Financial Services background preferred
Education:
• Bachelor's or Master's degree in computer science, statistics or related field is required (or relevant work experience)