Data Engineer

About The Company

The Judge Group is a leading professional services firm specializing in technology, talent, and business solutions. Renowned for its innovative approach and commitment to excellence, The Judge Group partners with organizations across various industries to deliver tailored staffing, consulting, and project management services. With a focus on fostering a collaborative and inclusive work environment, the company emphasizes continuous learning and growth for its employees.

Its extensive network and industry expertise enable it to connect talented professionals with impactful opportunities, driving success for both clients and candidates. The Judge Group values integrity, innovation, and a customer‑centric approach, making it a trusted partner in the ever‑evolving digital landscape.

We are seeking a highly skilled and motivated Data Engineer to join our dynamic team in Burlington, NJ, on a hybrid work basis. As a key member of our Enterprise Data and Analytics team, you will play a vital role in supporting various business units, including Merchandising, Allocations, Marketing, IT, and Supply Chain Analytics. Your primary responsibility will be to design, develop, and maintain robust data pipelines and architectures that enable advanced analytics, AI/ML applications, and real‑time data consumption.

This position offers an exciting opportunity to work with cutting‑edge technologies and contribute to the digital transformation initiatives of our organization.

The ideal candidate will have a strong background in data engineering, excellent communication skills, and a passion for leveraging data to drive business insights and innovation. You will collaborate closely with data scientists, analytics translators, and cloud engineers to ensure data accessibility, quality, and security. Your expertise will help shape the organization’s data strategy and facilitate data‑driven decision‑making across multiple departments.

• To be successful in this role, candidates should possess a Bachelor’s or Master’s degree in Computer Science, Engineering, Informatics, or related fields.
• A minimum of 5 years of experience in large‑scale data loading, processing, and analysis solutions is required.
• Candidates must have extensive experience with SQL‑based data processing and a solid understanding of data architecture, data warehouses, data lakes, and lake houses, with a focus on AI/ML techniques and large language models (LLMs).
• Proficiency with Snowflake, Oracle databases, Azure, and Azure Data Lake Storage (ADLS) is essential.
• Experience in developing and provisioning RESTful APIs for real‑time data access, source control tools such as Git Hub, and CI/CD pipelines is also required.
• Candidates should demonstrate expertise in data wrangling, normalization, and integration, along with familiarity with AI frameworks, GenAI, NLP, and streaming technologies like Azure Event Hubs, Kafka, and Spark Streaming.
• Additional preferred qualifications include experience with Informatica IDMC, Python or Java programming, enterprise schedulers, Dev Ops practices, Unix/Linux environments, and retail or CPG industry knowledge.
• Strong communication skills, strategic thinking, and a passion for innovation are critical to excel in this role.

• Design, develop, and maintain scalable ETL/ELT processes to extract data from various internal and external sources, ensuring data quality and consistency for analytics and AI applications.
• Lead the development of real‑time data pipelines to support high‑volume, low‑latency data consumption across different business units.
• Collaborate with analytics translators, data scientists, and cloud engineers to implement best practices in data architecture and management.
• Research and evaluate new data sources to enhance data accessibility, relevance, and comprehensiveness for business needs.
• Provide input and support for the design and implementation of cloud‑based data solutions, including data warehouses, lakes, and lake houses.
• Support operational activities related to data environments, including development, testing, deployment, and ongoing maintenance of data…