Job Overview
As a Data Engineer, you’ll build and maintain reliable data pipelines, platforms, and models that help teams turn complex information into useful insights. You’ll work across public cloud and big data systems, partnering with analytics and business intelligence teams to make data accessible, consistent, and ready for analysis.
Responsibilities
- Develop and maintain ETL (extract, transform, load) pipelines and data management integrations across cloud and SQL databases.
- Design data warehouses, data models, and dimensional models that support reporting and analytics.
- Integrate data through RESTful APIs and tools such as Informatica and Talend; manage queries and troubleshoot pipeline issues.
- Work with AWS, Azure Data Lake, Hadoop, Apache Hive, Spark, and linked data technologies to process big data.
- Your impact: Delivering trusted, well-organized data helps analysts and business teams make informed decisions.
Skills
- Essential: Data engineering, software development, SQL, Python, database design, data modeling, ETL pipeline development, and analysis skills.
- Essential: Experience with data warehouses, data warehousing design, SQL databases, cloud databases, and big data systems.
- Preferred: Java, Bash (Unix shell), shell scripting, Oracle, Microsoft SQL Server, Looker, and other business intelligence tools.
- Preferred: Agile practices, query management, model training, and experience with public cloud platforms, including AWS.
- Familiarity with Spark, Hadoop, Apache Hive, Azure Data Lake, Informatica, Talend, and linked data is valuable.
Pay: From $60.00 per hour
Work Location: In person
