Data Engineer

Only USC or GC profiles.

No. of Positions: 1

Employment Type : 3 months with possible extension

Bill Rate : $102.79/Hr.

Location: Arlington, Virginia

Job Title: Data Engineer

Hybrid – 3 days a week.

Must Have : High experience with Spark, SQL, Python and Hadoop

Must Have : Writing ETL jobs for getting data for different clients.

Developing new pipelines. On prem not much cloud.

Must Have : Write a lot of Spark jobs.

Job Description:

Overview: Client is seeking a Data Engineer II to contribute to the data management aspects of client engagements, delivering innovative solutions within the Services group. In this role, you will develop robust data pipelines, implement scalable data solutions, and collaborate with cross-functional teams. Additionally, you will help foster a high-performance, collaborative workplace culture. This hybrid position is based in Arlington, VA, requiring three days per week onsite. Client's Services organization aims to build industry-leading business experimentation software that brings sophisticated analytic techniques to business users around the world. We are rapidly expanding our product offerings and innovating on how we deliver solutions to our clients. Engineers work in small, flexible teams. Every team member contributes to designing, building, and testing features. There are no rigid organizational structures, and each team uses processes that work best for team members and projects.

Role:

• Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base.

• Develop scalable and efficient code to process data, ensuring availability and accessibility in a timely manner.

• Leverage big data processing frameworks such as Apache Spark and Hadoop to build and optimize data pipelines.

• Collaborate with senior engineers to address data challenges, contributing to solutions that maintain high data quality.

• Assist in the data delivery process, working alongside Data Engineers and Analysts to support accurate, high-value data solutions across various clients and industries.

• Build strong working relationships with team members and clients, contributing to both local and global projects.

• Learn and apply industry best practices, including version control, code reviews, and data validation, to ensure quality in data processes.

• Use SQL and other database technologies to help optimize data processing and reduce the time required to handle large data sets.

• Design, implement, and maintain data pipelines using ETL frameworks, orchestration tools, and distributed data processing engines.

• Participate in efforts to automate routine data tasks and streamline processes.

• Comply with all Client internal policies and adhere to external regulations.

Requirements

Must Have : High experience with Spark, SQL, Python and Hadoop

Must Have : Writing ETL jobs for getting data for different clients.

Developing new pipelines. On prem not much cloud.

Must Have : Write a lot of Spark jobs.