Senior Data Engineering Lead

Huntington National Bank•Columbus, OH
•Onsite

About The Position

The Data Engineer Senior Lead plays a pivotal role in building and operationalizing the data needed for enterprise data and analytics initiatives using industry-standard practices and tools. This position leads the design, development, and deployment of Data Engineering solutions that support enterprise goals, experimentation, and innovation, while serving as a technical leader. The role also directs efforts to ensure Huntington’s data conforms to business rules and is accurate, complete, consistent, and uniform. The Data Engineer Lead leads the development and deployment of solutions for valuable and challenging data-driven projects. The position sets direction for data engineering strategy and vision, oversees projects and data pipelines, and partners with data science, business analysis, and data governance teams. It provides technical leadership, coaching, and mentoring; plans and ensures execution of work and team goals; and collaborates with stakeholders to understand business needs. The role also evaluates technology trends and helps teams navigate 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.
  • Experience with 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 various 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 requirements 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 to the curated data catalog for governed reuse.
  • Provide leadership, coaching, and mentoring to team members, and develop the team to work with all areas of the organization.
  • Identify the roles, skills, and knowledge required to achieve organizational goals, and forecast new skill requirements.
  • Lead evaluation of tools with stakeholders across management levels to 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 ensure business needs are clearly understood and services meet those needs.
  • Anticipate and analyze technology trends and assess the impact of emerging technologies.
  • Coach individuals and teams through change and serve as a role model.
  • Perform other duties as assigned.
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