About the role

Data Engineer Lead managing data pipelines and analytics for enterprise initiatives while leading a team. Architecting and optimizing solutions to ensure data quality and business alignment.

Responsibilities

Architecting, creating and maintaining data pipelines
Assist with renovating the data management infrastructure to drive automation in data integration and management
Work in partnership with data science teams and with business analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements
Train counterparts across the organization in data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases
Work with data governance teams and participate in vetting and promoting content created in the business and by data scientists to the curated data catalog for governed reuse
Demonstrated ability to communicate complex results to technical and non-technical audiences
Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines
Strategic, intellectually curious thinker with focus on outcomes
Professional image with the ability to form relationships across functions
Provides leadership, coaching, and mentoring to team members, and develops team to work with all areas of the organization
Works with stakeholders to ensure that business needs are clearly understood and that services meet those needs
Anticipates and analyzes trends in technology while assessing the emerging technology’s impact(s)
Coaches' individuals through change and serves as a role model.

Bachelor's Degree in computer science, statistics or a related field
7+ years of related experience in data management disciplines including data integration, modeling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks
7+ years of experience with database programming languages and advanced analytics
Master's degree in computer science, statistics or related field (preferred)
Hands on data testing experience (preferred)
Demonstrated success working with data preparation tools (preferred)
Extensive experience with data engineering tooling (e.g., Glue, Landa, Athena, AWS) (preferred)
Expert knowledge of BI software tools (preferred)
Expert experience with open-source and commercial data science platforms (preferred)
Strong experience with various Data Management architectures and processes (preferred)
Strong ability to design, build and manage data pipelines for data (preferred)
Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets (preferred)
Demonstrated success in working with large, heterogeneous datasets to extract business value (preferred)
Strong experience in working with DevOps capabilities like version control, automated builds, testing and release management capabilities (preferred)