Hybrid Details: 2-3 days/week onsite
Duration: 2 months to start 

Job Duties:

• Technical Leader on the Data engineering team, defining IT Process and Technology strategies, familiarity with emerging technology trends, defining a roadmap and building consensus with Senior IT Leadership
• Help drive innovation by staying current with rapidly developing Data Engineering landscape and share knowledge internally and with customers
• Define and maintain data engineering strategy & roadmap, build consensus with Senior IT Leadership• Meet with Senior & Mid-Level Management to align business process initiatives and strategies with current and planned Penske Data Engineering & Analytics Architecture
• Evaluate Data Engineering & Analytics Tools/Techniques/ Approaches and determine impact on strategic objectives and manage overall implementation
• Be the primary contact and technical lead for multiple critical programs and integrations and resolve customer issues in a timely manner
• Effectively lead teams through the data engineering lifecycle (design, develop, test, release, and support) based on detailed requirements
• Collaborate with product owners and facilitate working sessions to acquire and understand requirements / acceptance criteria and translate into technical requirements
• Recommend conceptual designs and architecture, producing deliverables for multiple medium to large complex projects on time and under budget
• Lead the discovery and decision-making process when changes to standards and technology (tools, conventions, and design patterns)
• Play a leadership role in building data security and data governance guidelines
• Evaluate and research third-party packages and recommend customization and deployment opportunities as part of recommending a technical solution
• Own the architectural design of projects, provide expertise to project teams, and ensure adherence to established architectural standards and principles
• Provide constructive input and development opportunities for team members to department management
   

• 14+ years of overall technology experience required
• 12+ years of Data Engineering, Data Modeling, Data Warehousing, Master Data Management, Reference Data Management, Data Lineage, Data Governance and Meta Data Management experience required
• 7+ years of experience in defining Data & Analytics architecture implementing multiple large volume projects across onprem and oncloud environments. Preferably AWS.
• 5+ years of experience collaborating with Agile teams preferred
• Expertise in designing, validating, and implementing multiple projects across the hybrid infrastructure (On-cloud to On-Premises and vice versa)
• Expertise in setting up Data Lakes and analytical environments
• Expertise with Data Engineering tools such as Talend, BODS, Python, PySpark,Kafka,d API’s etc.
• Expertise with relational SQL and NoSQL databases
• Experience in building data pipelines, data ingestions, data integrations, data preparations, and traditional Data warehouses and Datamarts
• Experience in building processes supporting data transformation, data structures, metadata, dependency, and workload management
• Strong experience with data modelling techniques utilizing tools such as Erwin, ER Studio etc.
• Experience with visualization tools such as QlikView, Qlik Sense, Tableau, etc.
• Experience in message queuing, stream processing, and highly scalable ‘big data’ data stores
• Experience with big data tools such as Kafka
• Strong analytic skills related to working with complex datasets
• Expert knowledge of appropriate design frameworks and patterns and experience in implementing them
• Ability to consistently develop knowledge of industry wide technology strategies and best practices
• Able to communicate highly technical concepts in clear/concise manner to non-technical individuals
• Experience prioritizing technology needs within set budget requirements
• Excellent interpersonal and decision-making skills