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Data Warehouse Senior Program Manager/Technical Team Management
Data Warehouse Senior Program Manager/Technical Team ManagementCentral Point Partners • Columbus, Ohio Metropolitan Area, United States
Data Warehouse Senior Program Manager / Technical Team Management

Data Warehouse Senior Program Manager / Technical Team Management

Central Point Partners • Columbus, Ohio Metropolitan Area, United States
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Title : Data Warehouse - Sr. Program Manager (Manager of Technical Teams)

JobID # : 7871

Company : Huntington National Bank

Position Type : Right to Hire (Direct Hire after 3 months contract)

Pay Rate : $140000 - $155000+ / Year + 20% annual bonus + eligibility for Stock Grants

Location : Columbus, OH - Hybrid role (4 days / week onsite, 1 day remote)

Must have managerial experience with direct reports in the Data warehouse environment.

Prefer applicants with experience in banking, healthcare or other regulatory industry.

Huntington Bank is looking for a data warehouse leader in our Data Technology organization. In this role you will lead a team of 12-16 dedicated to pushing the limits of continuous improvement and innovation using data warehousing as a lever. You will be responsible for leading within the Enterprise Data Warehouse for the bank, including innovating on the platform to enable next-generation capabilities. You will participate in the definition of the strategic roadmap for data technology and be responsible for executing data warehousing initiatives. You will partner with other Data Technology organizations and CDAO leads to architect and enable an effective data ecosystem, as well as key leaders in business and technology to understand and support their needs.

Basic Qualifications

  • Bachelor's degree in a related field.
  • 10+ years of hands-on experience in managing multi-terabyte data warehousing engineering projects.
  • 6 -7 + years of experience as a technology manager with direct reports for data warehouse teams.
  • Deep understanding of enterprise data warehousing best practices for technical implementation and providing business value. Thought leadership in next-evolution modern data architectures. Best practice EDW testing and validation approaches and implementation.
  • Strong organizational skills with demonstrated ability to build and manage a high-performing team, work with partners to set and meet business service level agreement levels, plan and deliver work to expectations.
  • Strong communication and interpersonal skills for interacting and collaborating with developers, analysts and business colleagues throughout the organization.
  • Prefer experience working in Banking, Healthcare, or any other regulated industry environment.

Preferred Qualifications (Nice to have)

  • Experience / understanding of any cloud technologies (AWS, Snowflake or others)
  • Experience / understanding of / IBM DataStage, Python PySpark, Erwin Enterprise Data Modeler and / or Tableau.
  • Experience with data governance and data management approaches, including data quality.
  • Experience with business intelligence and advanced analytics.

    • Key Responsibilities

  • Lead a team of 12-16 resources, providing strategic direction, coaching, and technical oversight.
  • Drive agile execution, ensuring consistent velocity, transparency, and stakeholder engagement.
  • Execute the EDW technology strategy, ensuring alignment with enterprise goals and segment priorities.
  • Participate in demand management and planning, assessing impact, feasibility and estimating work effort.
  • Understand and translate the technical design from the Data Architect team into implemented physical data models that meet data governance, enterprise architecture and business requirements for data warehousing. Manage data within the data warehouse to ensure efficiency of platform.
  • Work with operational data and data acquisition teams to manage incoming sources and the down-stream systems to understand and support their needs for reporting and analytics.
  • Support incident resolution and continuous improvement to drive efficiency across multiple operational run metrics.
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