Data Engineer/ETL Developer

Job Description: Data Engineer / ETL Developer

Location:
Remote (with occasional client travel as needed)

Experience Level:
Mid to Senior

Overview

Wize Solutions, a leading IT consulting firm based in Abingdon, VA, is seeking a Data Engineer/ETL Developer. As a core member of our Data Engineering team, you will design, develop, and maintain secure, reliable ETL solutions supporting critical business processes across multiple business units. You will work in complex, multi-platform environments and collaborate with cross-functional teams to deliver scalable data solutions and actionable insights.

Qualifications

• Strong understanding of Data Warehousing concepts (Dimensional Modeling, ETL, etc.) and RDBMS principles
• Minimum 5 years of hands-on experience with Talend ETL tool
• Minimum 5 years of experience in SQL, including Stored Procedures and Table Design
• Minimum 5 years of experience in SQL Query optimization and ETL Data loading performance
• Minimum 2 years of experience with Snowflake Cloud Data Warehouse
• Experience as a Data Engineer on Hadoop platforms (HIVE, KAFKA, NiFi, Spark, etc.) is a big plus
• Minimum 2 years of experience in shell scripting
• Experience with real-time streaming technologies preferred
• Experience deploying machine learning models and automating processes in production is a plus
• Experience with cloud technologies (AWS, Azure, GCP) is a big plus

Responsibilities

• Design, develop, and maintain secure, consistent, and reliable ETL solutions supporting critical business processes across various business units
• Ensure data solutions are compliant with enterprise security standards
• Work in complex multi-platform environments on multiple project assignments
• Develop and perform tests, validate data flows, and prepare ETL processes to meet complex business requirements, including designing and implementing complex end-to-end solutions using BI platforms
• Coordinate with analysts and developers to ensure jobs meet minimum support standards and best practices before migration into production
• Partner with infrastructure teams, application teams, and architects to generate process designs and complex transformations, providing business insights
• Use strategies such as indexing and partitioning to fine-tune data warehouse and big data environments, improving query response time and scalability
• Define and capture metadata and rules associated with ETL processes
• Assist production support teams in resolving production job failures, data issues, and performance tuning

Note:
ETL development and process support may require weekend or off-business hours work.