Lead Data Engineer

TEKsystems•Westerville, OH

28d•$60 - $85•Hybrid

About The Position

This role will be supporting M&A data intake due to Cadence Bank acquisition. This person must be local to Columbus, OH. There will not be daily/weekly expectations to be onsite, but they must be local for meetings onsite at Huntington. Huntington will be intaking customer data from Cadence Bank acquisition. This will be a true contract role to start. There is currently a fulltime employee doing this work that has too much work responsibility day-to-day and can no longer support this work. There is an opportunity to extend or convert to fulltime depending on future Huntington priorities. Summary: This role plays a pivotal role in building and operationalizing the minimally inclusive data necessary for the enterprise data and analytics initiatives following industry standard practices and tools. Data Engineers will also test for data quality to ensure Huntington’s data conforms to business rules and is accurate, complete, consistent, and uniform. This role’s primarily focuses on building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for key data and analytics consumers like business/data analysts, data scientists or any persona that needs curated data for data and analytics use cases across the enterprise. Duties and 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. Performs other duties as assigned.

Requirements

Python
Sql
Aws
lambda
Athena
terraform
Data
Bachelor's Degree in computer science, statistics or related field, or equivalent related work experience.
4+ 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
4+ years of experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative, experience with data preparation tools and database programming languages
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
Willingness and ability to learn new technologies on the job

Nice To Haves

Master's degree in computer science, statistics or related field
Hands on data testing experience
Strong experience with data engineering tooling (e.g., Glue, Landa, Athena, AWS)
Strong experience with open-source and commercial data science platforms
Learn and/or Agile methodology
Strong experience with various Data Management architectures and processes
Strong ability to design, build and manage data pipelines for data
Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets
Demonstrated success in working with large, heterogeneous datasets to extract business value
Strong experience in working with DevOps capabilities like version control, automated builds, testing and release management capabilities

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.
Performs other duties as assigned.