REL 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 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 Data Factory and SQL Server Integration Services.
• 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.
• Proficient in querying MongoDB and integrating data across database systems for efficient data retrieval and processing.
• Ensure data quality and performance at scale.
• Ensure high performance and scalability of data systems and processes.
• Help with the collection, connection, and storage of data.
• Optimize existing data workflows and ensure system reliability.
• Collaborate with team members and 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 language.
• Advanced understanding of API frameworks and JSON transformations.
• Understanding of various data warehousing architectures (Mongo, Azure, SQL, etc.).
• Basic understanding of business and operating environment.
• Basic knowledge of programming languages (Mongo, Python, PowerShell, R, SQL, C#).
• Experience with data management, processing and analytic tools (Databricks).
• Experience with data integration and processing tools.
• Basic problem-solving skills.
• Basic communication and collaboration skills.
• Working experience with data warehousing solutions, ETL tools, and data system design.
• Basic knowledge of data engineering principles, technologies, and architecture.