Data Engineer II

6 days ago

Reading, Pennsylvania, United States Penske Full time
About the Role

We are seeking a highly skilled Data Engineer II to join our team at Penske. As a Data Engineer II, you will be responsible for leading the development, enhancement, and support of existing and new data pipelines, data ingestions, data storage, and traditional Data-warehouse/BI systems across medium and large-sized projects concurrently.

Key Responsibilities
  • Lead the effort to develop, enhance, and support existing and new data pipelines, data ingestions, data storage, and traditional Data-warehouse/BI systems.
  • Support software developers, database architects, data analysts, and data scientists on vital initiatives and ensure optimal data delivery architecture consistent throughout ongoing projects.
  • Influence our data and analytics roadmap by constant interactions with various business and technology teams.
  • Lead the design of vital components and suggest/implement new frameworks and tools based on industry and technological trends and advances.
  • Consult with process owners in reviewing, interpreting, and developing systems in accordance with user requirements and ensuring code quality through proper documentation, best practices, and code reviews.
  • Provide day-to-day task leadership and project reviews.
  • Assemble large, complex data sets that meet functional/non-functional business requirements.
  • Produce deliverables for medium to large-sized projects with clean, well-documented, and easily maintainable code that adheres to defined coding standards.
  • Design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  • Build and leverage the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources both on-premise and cloud.
  • Partner with cross-functional teams to build analytics tools that utilize the data pipeline to provide actionable insights into key business performance metrics.
  • Participate in building data security and data governance guidelines.
  • Ensure solution is sustainable across implementation and use, troubleshooting and analyzing open issues and bug-fixes, and ensuring on-time delivery and hand-offs.
  • Communicate status and issues to team members and stakeholders.
  • Participate in Design and Deploy Tollgate reviews and gain buy-in from cross-functional teams including QA, Architect, Security, Webmaster, and Operations.
  • Contribute and influence the discovery and decision-making process when changes to standards and technology are required (tools, conventions, and design patterns).
  • Assign projects and review deliverables from onshore and offshore software engineers.
  • Provide constructive input to department management regarding team members assigned to projects.
  • Independently conduct new hire interviews.
  • Design and manage models to handle large datasets of existing structured and unstructured data.
  • Research and discover new methods to acquire data and new applications for existing data.
  • Stay current with rapidly developing Data Engineering landscape and share knowledge internally and with customers.
  • Create recommendations for increasing data utilization based on understanding of data delivery environment.
Qualifications
  • Bachelor's Degree in Computer Science/Computer Engineering or equivalent years of software development experience required.
  • 10+ years of overall technology experience.
  • 8+ years of Data Engineering, Data Modeling, and Data Warehousing experience required.
  • 2+ years of experience working with Agile teams preferred.
  • 1-2 years of experience leading medium to large projects.
  • Expert knowledge of full data engineering lifecycle.
  • Expert experience with Data Engineering tools such as Talend, BODS.
  • Strong experience with relational SQL and NoSQL databases.
  • Expert experience in building data pipelines, data ingestions, data integrations, data preparations, and traditional Data warehouses and DataMarts.
  • Strong experience in building processes supporting data transformation, data structures, metadata, dependency, and workload management.
  • Strong analytic skills related to working with complex datasets.
  • Expertise in designing, validating, and implementing multiple projects across the hybrid infrastructure (On-cloud to On-Premise and vice versa).
  • Experience with big data tools such as Kafka.
  • Some experience with visualization tools such as Qlikview, Qliksense, Tableau, etc.
  • In-depth knowledge of appropriate design frameworks and patterns and experience in implementing them.
  • Knowledge of industry-wide technology strategies and best practices.
  • Understanding of message queuing, stream processing, and highly scalable 'big data' data stores.
  • Solid written and oral communication skills; ability to present ideas in business-friendly and user-friendly language.

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