Senior Data Engineer

Job Title: Senior Data Engineer

Location: Columbus Ohio 43219 (4 days Onsite, 1 day remote)

Type: 3 Months Contract to Hire

Contract only W2

Overview:

Our Enterprise Data Engineering department is growing, and we're looking for an outstanding Senior Data Engineer to join our team. The Senior Data Engineer will play 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. Our goal is to be the Best performing Regional Bank in America, and we need data and analytics to meet that goal.

Responsibilities:

• Architecting, creating, and maintaining data pipelines

2. Assist with renovating the data management infrastructure to drive automation in data integration and management

3. 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

4. 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

5. 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

6. Demonstrated ability to communicate complex results to technical and non-technical audiences

7. Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines

8. Strategic, intellectually curious thinker with focus on outcomes

9. Professional image with the ability to form relationships across functions

Skills:

• Strong experience with various Data Management architectures and processes

2. Strong ability to design, build and manage data pipelines for data

3. Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures, and integrated datasets

4. Demonstrated success in working with large, heterogeneous datasets to extract business value

5. Strong experience in working with DevOps capabilities like version control, automated builds, testing, and release management capabilities

6. Demonstrated ability to communicate complex results to technical and non-technical audiences

7. Demonstrated ability to work effectively in teams as well as independently across multiple tasks while meeting aggressive timelines

8. Strategic, intellectually curious thinker with focus on outcomes

9. Professional image with the ability to form relationships across functions

10. Willingness and ability to learn new technologies on the job

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

2. 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

3. Strong experience with advanced analytics tools

4. Hands on data testing experience

5. Strong experience with data engineering tooling (e.g., Glue, Landa, Athena, AWS)

6. Strong knowledge of BI software tools

7. Strong experience with open-source and commercial data science platforms

8. Learn and/or Agile methodology

         • Financial Services background preferred

Education:

               • Bachelor's or Master's degree in computer science, statistics or related field is required (or relevant work experience)

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