What are the responsibilities and job description for the Mid-level Data Engineer position at Credence company?
Overview :
Credence Management Solutions, LLC (Credence) is seeking a mid-level Data Engineer to join our Technology Practice. This position will provide an opportunity to work with an experienced team of Cloud Engineers, Solutions Architects, Data Scientists, Developers, and Cybersecurity professionals. The candidate will have the opportunity to grow their career in the Cloud and Data Science spaces by honing their cloud and data science knowledge and skillsets. This position is based in Credences corporate headquarters located in Tysons Corner in Vienna, VA.
We are seeking a motivated and skilled mid-level Data Engineer to join our team. The ideal candidate should be passionate about data engineering, possesses a strong analytical mindset, and demonstrate a keen interest in working with large-scale data systems. In this role, you will assist in designing, developing, and maintaining our data pipelines, ensuring the efficient flow of data between various systems. You will collaborate closely with cross-functional teams, including data scientists, cloud engineers, software engineers, and business analysts, to enable data-driven decision-making and deliver high-quality solutions.
Responsibilities include, but are not limited to the duties listed below :
- Assist in designing, developing, and maintaining data pipelines, ensuring smooth data flow from diverse sources into our data warehouse.
- Collaborate with data scientists and software engineers to implement efficient and scalable data processing solutions.
- Perform data cleansing, transformation, and aggregation to ensure data integrity and accuracy.
- Help optimize and tune data pipelines for performance and reliability.
- Assist in monitoring and troubleshooting data-related issues to ensure smooth operations.
- Collaborate with cross-functional teams to understand data requirements and translate them into technical solutions.
- Stay up-to-date with emerging data engineering technologies and best practices to contribute innovative ideas and improvements.
- Document data engineering processes, procedures, and standards for future reference.
Education, Requirements and Qualifications :
Nice to Have
