Company:
1872 Consulting
Location: Chicago
Closing Date: 31/10/2024
Salary: £100 - £125 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description
Data Engineer
Chicago, Dallas or NY - hybrid WFH
Why This Role Is Valuable
This person will sit on a more senior Data Engineering team and have ample opportunity to learn modern data engineering technologies such as Spark/PySpark and working in modern cloud environments, with cloud DWs.
While you must have the core ETL/Data Engineering experience, we want more junior engineers who are eager to learn and grow in their careers.
What you'll be doing
Chicago, Dallas or NY - hybrid WFH
Why This Role Is Valuable
This person will sit on a more senior Data Engineering team and have ample opportunity to learn modern data engineering technologies such as Spark/PySpark and working in modern cloud environments, with cloud DWs.
While you must have the core ETL/Data Engineering experience, we want more junior engineers who are eager to learn and grow in their careers.
What you'll be doing
- Design, develop, and launch extremely efficient and reliable data pipelines to move and transform data to enable downstream consumption and insights.
- Collaborate with other data engineers, analysts, product managers, and customers to implement technical solutions to business problems.
- Support the development process by participating in regular scrum activities, code review, and architectural reviews.
- Implement DevOps patterns in conjunction with our SREs.
- Diagnose and solve issues in existing data pipelines and use learnings to build their successors.
- 2+ years of experience with Data Engineering, Data Analysis, and/or ETL Development.
- Must have at least 1 year of experience with Data Engineering (building data pipelines) OR ETL Development experience, as data engineering is the focus of this role.
- Must have strong SQL experience.
- Must have at least some experience working in cloud environments, ideally Azure.
- Spark/PySpark experience.
- Python experience.
- Experience with the issues of performance, availability, scalability, reliability, and maintainability of data pipelines.
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1872 Consulting
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