Location: Hershey, PA

This position can sit remotely.

 

 

Overview:

 

The Enterprise Data organization drives value for Hershey by providing high-quality, well governed data to the Enterprise for analytics and decision-making.  The leader within Data Engineering will be responsible for owning the enterprise data engineering activities, including the execution, strategy and upskilling.  Working with IT product owners and business stakeholders, the incumbent will ensure their data solutions meet expectations and requirements.   In addition, the leader will be an active member of a governing body/council, to collaborate the maturing and growth of the governing procedures and incorporate those procedures into an evolving governance model. ​

 

 

Major Responsibilities:

 

Enterprise Data Strategy:  Lead the IT Data Engineering function, creating the strategic roadmap and delivering the project portfolio in partnership with product owners and strategists.  Data Engineering Domain: Collaborate with IT and business partners to define, manage and deliver innovative Data solutions to drive growth and adoption of capabilities at Hershey.  Mentoring and Coaching: Manage the data engineering team, ensuring success through formal and informal education, development, mentorship, and innovative thought leadership. Builds and executes the strategy to deliver cloud-based intelligent systems to collect, distribute, model, and analyze disparate and diverse data assets to automate insights and drive business performance. Works closely with leaders within data architecture, enterprise architecture, data science and domain experts, to build and maintain roadmaps against the IT strategy.  Own the delivery of a modern data engineering model that follows Dev/Ops principles and standards for continuous integration/ continuous delivery (CI/CD) processes.  Co-Lead the deployment, maintenance and adoption of a modern data platform and integration toolset that aligns to the data engineering and operations principles.  Engage with project teams to understanding a project’s needs/requirements to provide resourcing and leadership to deliver on project goals and timelines. Strategic thinker with holistic vison, specific focus on the identification for the automation of existing manual processes to drive key business performance. Lead the coaching and upskilling of the data engineer and data engineering operations teams for new and existing tools within the Enterprise Data ecosystem.  Ensure reliability in data and data pipelines, enforcing governance, security, and performance. Establish best in class key performance indicators to measure the performance of the data engineering teams and processes.  

 

 

Qualifications:

 

 

Demonstrated leadership and managerial skills. Excellent verbal and written communication skills. Strong financial and contract management and analytical skills especially in a technical environment. Excellent Program and Project management skills. Strong problem solving and analytical skills. Excellent customer service skills. Excellent understanding of corporate policies, practices and organizations. Strong negotiation skills and contract requirements. Extensive experience managing external resources. Ability to manage multiple priorities, meet deadlines and produce quality results under pressure. High energy self-starter.

 

 

Education/Experience Requirements:

 

 

Bachelor’s in a STEM degree. Master’s degree and/or related equivalent experience preferred. 13+ years of progressive experience working with data, five to seven of which has been focused in leading cross-functional teams and enterprise-wide data management programs.  10+ years of experience in building data solutions within an enterprise environment using industry standard guiding principles and practices. 7+ years of experience with SQL, Python, Scala and Spark languages to explore, interact and build solutions. 4+ years of experience with public and private cloud solutions, including building and maintaining a data ecosystem that includes an ERP environment. Advanced working knowledge and experience with relational/non-relational databases e.g. Teradata, Snowflake, Databricks, Azure Data solutions and Hadoop. Experience working with machine learning and data science teams. Experience building data visualizations or analytics e.g. Power BI, Tableau, SSRS, SAP. Excellent communication and presentation skills, with the ability to articulate new ideas and concepts to technical and non-technical partners. Experience leading a project team or project function to deliver a large-scale enterprise data, application and/or ERP solution. Experience with COBIT/SOX, as well as PII data in accordance with relevant laws. Strong team builder, change agent, and motivator.

 

 

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