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Mid-level Data Engineer

2 months ago

McLean, United States Credence Management Solutions, LLC Full time

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 Credence’s corporate headquarters located in Tyson’s 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

US citizen with ability to obtain a DoD Public Trust or higher is required.
Bachelor's degree in Computer Science, Information Systems, Economics, or a related critical thinking field. Equivalent practical experience will also be considered.
Three to Eight (3-8) years of relevant experience
Understanding of data engineering concepts and principles (ingestion, standardization, transformation)
Proficiency in programming languages such as Python, Java, or Scala.
Experience with SQL and relational databases.
Familiarity with data modeling and ETL/ELT (Extract, Transform, Load) processes.
Basic understanding of distributed computing and big data technologies such as Apache Hadoop, Spark, or Kafka.
Knowledge of cloud-based data storage and processing platforms like AWS, Azure, or Google Cloud is a plus.
Excellent problem-solving and analytical skills.
Strong communication and teamwork abilities.
Attention to detail and commitment to delivering high-quality work.
Ability to work in a fast-paced environment and handle multiple tasks simultaneously.

Nice to Have

Familiarity with DevOps scripting languages (Gitlab CI/CD)
AWS Cloud Practitioner or AWS Associate Level Certification
Experience automating tasks in a cloud or on premise environment