Senior Data Engineering Lead

Huntington National Bank•Columbus, OH

4d•Onsite

About The Position

The Senior Data Engineering Lead will build and operationalize the data needed for enterprise data and analytics initiatives using industry-standard practices and tools. This role leads the design, development, and deployment of data engineering solutions that support enterprise goals, experimentation, innovation, and challenging data-driven projects. It also directs efforts to ensure Huntington’s data conforms to business rules and is accurate, complete, consistent, and uniform. The role sets direction for data engineering strategy and vision, leads data engineering projects and teams, and partners with data science, business analysis, and data governance teams. It provides technical leadership, coaching, and mentoring while helping ensure that business needs are understood and services meet those needs. The position also evaluates technology and tools, plans and oversees execution of work, and helps teams adapt to change.

Requirements

Bachelor’s degree in computer science, statistics, a related field, or relevant work experience.
10+ 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.
10+ years of technical leadership and experience with data-centric products, database programming languages, and advanced analytics tools.

Nice To Haves

Master’s degree in computer science, statistics, or a related field.
Expert experience with data engineering tooling such as Glue, Landa, Athena, and AWS.
Expert knowledge of BI software tools.
Expert experience with open-source and commercial data science platforms.
Knowledge of Lean and/or Agile methodology.
Demonstrated ability to influence technical and non-technical audiences.
Demonstrated participation and leadership in the broader technology community.
Ability to foster an inclusive and innovative working environment.
Demonstrated negotiation, influencing, partnership, presentation, and communication skills.
Ability to understand business challenges and translate them into value-added, data-driven solutions.
Strong experience with data management architectures and processes.
Strong experience working with large, heterogeneous datasets to build and optimize data pipelines, pipeline architectures, and integrated datasets.
Demonstrated success working with large datasets to extract business value.
Strong experience with DevOps capabilities such as version control, automated builds, testing, and release management.
Strategic, intellectually curious thinker with a focus on outcomes.
Professional image and ability to form relationships across functions.
Ability to train more junior analysts regarding day-to-day activities, as necessary.
Proven ability to lead cross-functional teams.
Willingness and ability to learn new technologies on the job.
Financial Services background.

Responsibilities

Lead data engineering projects and efforts.
Help set the strategy and vision for data engineering.
Lead the architecture, creation, and maintenance of data pipelines.
Partner with data science teams and business analysts to refine data requirements and data consumption needs for data and analytics initiatives.
Work with data governance teams and participate in vetting and promoting content created in the business and by data scientists into the curated data catalog for governed reuse.
Provide leadership, coaching, and mentoring to team members, and develop the team to work across the organization.
Identify the roles, skills, and knowledge needed to achieve organizational goals and forecast new skill requirements.
Lead tool evaluations with stakeholders across management levels, prioritize analytics use cases and requests, and maintain the overall book of work.
Plan and ensure execution of work and achievement of team goals.
Work with stakeholders to understand business needs and ensure services meet those needs.
Anticipate and analyze technology trends and assess the impact of emerging technology.
Coach individuals and teams through change and serve as a role model.
Perform other duties as assigned.