JOB DESCRIPTION
Job Title: DATA ENGINEER II
Summary/Objective: Data Engineer II will be responsible for developing and maintaining data storage, processing, and deployment systems and processes. Their duties include coordinating with IT management and other professionals to create unique data infrastructure, running tests on their designs to isolate errors, and updating systems to accommodate changes in company needs.
Essential Functions/Responsibilities:
- Connect dots and communicate gaps up stream to supporting teams, as well as downstream to consumers
- Assist with corporate wide reporting and dashboard needs
- Assembling large, complex sets of data that meet non-functional and functional business requirements
- Identifying, designing, and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
- Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS and SQL technologies
- Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
- Working with stakeholders including data, design, product, and executive teams and assisting them with data-related technical issues.
*The responsibilities as defined are intended to serve as a general guideline for this position. Associates may be asked to perform additional tasks depending on strengths and capabilities. *
Required Experience:
- 3+ years’ experience in a Data Engineering role.
- Must be a self-starter with strong leadership skills.
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Excellent communication skills and demonstrated problem-solving ability.
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Detail oriented, excellent problem solving, multi-tasking, and investigation skills.
- Excellent interpersonal skills in relating to both internal and external customers.
- Experience with both analytical and transactional database systems.
- Experience in different database management systems, such as Redshift, Snowflake, SQL Server, PostgreSQL, MySQL, MongoDB, etc.
- Experience in building data models for both analytical and transactional purposes.
- Experience in SQL.
- Experience in Python or R, along with the associated data libraries, such as PySpark, Pandas, etc. Python is preferred.
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Experience in AWS ecosystem.
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Product, Process, Tooling, and alternative manufacturing method knowledge preferred.
Preferred Education:
- Masters’ Degree in Business, Data Science, Natural Science, or Engineering is preferred.
- Experience can be substituted for educational requirements.
- Advanced English level (mandatory).
