Data Warehouse Sr. Manager

Huntington Bancshares
Columbus, United States of America
15 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote
Columbus, United States of America

Tech stack

Amazon Web Services (AWS)
Cloud Computing
Data Architecture
Data Governance
Data Integration
Dataspaces
Data Warehousing
Python
Operational Data Store
Technical Data Management Systems
Enterprise Data Management
Snowflake
Data Lake
PySpark
Data Management
Physical Data Models

Job description

Huntington Bank is looking for a data warehouse leader in our Data Technology organization. In this role you will lead a team of 12-15 dedicated to pushing the limits of continuous improvement and innovation using data warehousing as a lever. As a Sr. Manager of the Data Warehouse, you will report to the Data Warehouse Director and work closely with the Chief Data & Analytics Office to influence the business and technology strategies for the company.

If you consider data as a strategic asset, evangelize the value of good data and insights, have deep understanding of data governance, are an experienced thought leader in data warehousing and love building teams and mentoring talent, this role is for you.

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., * Manage a team of colleagues and contractors, providing resource allocation, coaching and development.

  • Lead a cross functional agile team to deliver on projects, providing thought leadership and technology oversight.
  • ·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., Certain positions outside our branch network may be eligible for a flexible work arrangement. We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Requirements

  • Bachelor's Degree
  • 10+ years of hands-on experience in multi-terabyte data warehousing engineering projects.
  • 7+ years of experience as a technology manager for data warehouse teams.

Preferred Qualifications:

  • 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.
  • Proven ability to take requirements and logical designs and translate them into physical implementation, informed by business and enterprise requirements.
  • Experience with traditional data architecture: operational data stores, sourcing and staging data, data integration, master data management, dimensional/snowflake and de-normalized design, managed views, datamarts and analytical sandboxes.
  • Experience with cloud technologies including AWS and Snowflake.
  • Experience with DataLake, Python/PySpark, Erwin Enterprise Data Modeler.
  • Experience with data governance and data management approaches, including data quality.
  • Experience with business intelligence and advanced analytics.

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