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Customer Job

Data Engineer III

Job ID: 25-11573
Pay rate range - $75/hr. to $80/hr. on W2
Fully Onsite

Must Have
Strong experience with SQL
Experience in at least one modern scripting or programming language, such as Python, Java.
Experience with data modeling, warehousing and building ETL pipelines

Required Skills & Experience
- 7+ years of related experience.
- Experience with data modeling, warehousing and building ETL pipelines
- Strong experience with SQL

- Experience in at least one modern scripting or programming language, such as Python, Java.
- Strong analytical skills, with the ability to translate business requirements into technical data solutions.
- Excellent communication skills, with the ability to collaborate across technical and business teams.
- A good candidate can partner with business owners directly to understand their requirements and provide data which can help them observe patterns and spot anomalies.

Preferred
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- 3+ years of reparation of data for direct use in visualization tools like Tableau experience
 

Responsibilities
* As a Data Engineer you will be working in one of the world's largest and most complex data warehouse environments.
* You will be developing and supporting the analytic technologies that give our customers timely, flexible and structured access to their data.
• Design, build, and maintain scalable, reliable, and reusable data pipelines and infrastructure that support analytics, reporting, and strategic decision-making.
* You will be responsible for designing and implementing a platform using third-party and in-house reporting tools, modeling metadata, building reports and dashboards
* You will work with business customers in understanding the business requirements and implementing solutions to support analytical and reporting needs.
• Explore source systems, data flows, and business processes to uncover opportunities, ensure data accuracy and completeness, and drive improvements in data quality and usability.

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