Senior Data Engineer

Location: Hershey, PA - local candidates only
Position Type: 100% Onsite
Contract Length: 4 months
Qualifications:

• 5-8 years of experience
• SQL, Databricks, Snowflake, Power BI are required
• Industry Experience: CPG preferred
• Experience designing, implementing large scale data pipelines for data curation, feature engineering and machine learning across multiple environments
• Working knowledge of agile frameworks
• Ability to manage multiple priorities, meet deadlines and produce quality results under pressure
• Demonstrated leadership and managerial skills
• Strong problem solving and analytical skills
• Strong team player, change agent, and advocate
• Excellent customer service skills
• High energy self-starter
• Excellent verbal and written communication skills

Responsibilities: Time % Summary of major duties:
1. 60% Data Engineering Solution Delivery:
Develop and deliver high-quality data pipelines adhering to best practice, privacy, and governance principles
2. 20% Data Engineering Maintenance/Optimization:
Work existing data pipelines and solutions to enhance its performance, quality and/or functionality. Resolve incidents escalated by support teams or business users
3. 10% 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
4. 10% Data Engineering Advocacy:
Evangelize future data solutions identified by Enterprise Data leadership, including innovations such as: metadata management; data security and governance; cloud-based systems for data storage; multi-environment integration and automation of data tasks and movement
 
Specific Job Responsibilities:
• 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
• Using best practice frameworks and governance, evaluate, design, and analyze solution engineering for agile delivery
• Create and develop robust and secure ETL pipelines across a broad range of data-focused products, services, projects, and systems
• Using best practice guidance from Enterprise Data leadership, oversee the health and evolution of agile execution team engineering technologies
• Works closely with leaders within data engineering, data architecture, data science and domain experts, to build and maintain roadmaps against the IT strategy
• Partner to deliver a modern data engineering model that follows Dev/Ops principles and standards for continuous integration/ continuous delivery (CI/CD) processes
• Ensure reliability in data and data pipelines, enforcing governance, security, and performance
• Collaborate in developing best in class key performance indicators to measure the performance and quality of the data engineering teams and processes
• Able to articulate the holistic benefits of data engineering from a business perspective, while maintaining the relationship with business analysts, data scientists, technical engineers, and project managers