Associate Data Engineer

Job Description:

Design, develop, and optimize data pipelines and systems for efficient data collection, integration, and storage. Interpret data to generate insights and implement reliable data processing workflows that ensure data quality and system stability. Apply data governance practices across ETL pipelines, metadata management, security, and lineage tracking. Develop an understanding of business objectives to align data solutions and address increasingly complex data challenges while building proficiency in standard procedures and techniques.

Responsibilities:

• Develop and maintain data pipelines and workflows using Azure Data Factory and SQL Server Integration Services (SSIS).

• Format data from APIs into SQL servers.

• Collaborate with stakeholders to gather data requirements and ensure alignment with business needs and objectives.

• Design and build data pipelines for data collection, connection, and storage.

• Develop and enforce data engineering policies and best practices to ensure data integrity.

• Query data from MongoDB and integrate across database systems for efficient data retrieval and processing.

• Ensure data quality, performance, and scalability of data systems and processes.

• Optimize existing data workflows and ensure system reliability.

• Support data collection, connection, and storage initiatives.

• Collaborate with team members and actively participate in team projects and initiatives.

Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.

• 3 5 years of experience in data engineering and governance.

• Advanced knowledge of SQL.

• Advanced understanding of API frameworks and JSON transformations.

• Understanding of various data warehousing architectures (e.g., MongoDB, Azure, SQL).

• Basic understanding of business and operating environments.

• Basic knowledge of programming languages such as Mongo, Python, PowerShell, R, SQL, and C#.

• Experience with data management, processing, and analytics tools (e.g., Databricks).

• Experience with data integration and processing tools.

• Basic problem-solving and analytical skills.

• Effective communication and collaboration abilities.

• Working experience with data warehousing solutions, ETL tools, and data system design.

• Foundational knowledge of data engineering principles, technologies, and architecture.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.