Full-Stack Engineer

We are seeking a skilled Full-Stack Engineer with knowledge and experience in both Development and Data. This role combines technical expertise and a deep understanding of business processes to deliver impactful business solutions. The ideal candidate will have extensive experience in building scalable data pipelines, automating data processes, and be able to contribute to projects from beginning to end and achieve business objectives.

• Develop and maintain robust data pipelines to collect, transform, and process large datasets from various sources, ensuring timely and accurate delivery of data for analytics and reporting.
• Work with the Lead Engineer to automate business processes, automate the movement of data within the organization, and orchestrate the exchange of data with external partners.
• Collaborate with other department managers and business leaders to complete organizational goals and strategic priorities and support critical processes.
• Optimize data architecture and performance by leveraging modern technologies and by implementing performance-tuning strategies for databases, procedures, and functions.
• Automate data workflows to improve efficiency and scalability, while ensuring data integrity, hygiene, and cost efficiency.
• Work closely with business stakeholders to gather requirements, translate them into technical specifications, and deliver solutions within project timelines.
• Troubleshoot and resolve data and reporting issues , driving continuous improvement in analytic capabilities.

Qualifications

• Bachelor's degree is preferred in Computer Science, Data Engineering, related field or 10+ years of experience.
• A proven track record in building scalable data pipelines and automating data processes through programming, scripts, APIs, and platform tools.
• Expertise in modern data tools and technologies , including SQL Server, Microsoft Fabric, Data Bricks, Azure Functions, ADF, Synapse, Python, C# / .NET, and APIs.
• Strong experience in performance tuning databases, procedures, and functions, with a focus on optimizing data architecture, scalability, and cost savings.
• Deep understanding of data integrity and hygiene , with a commitment to maintaining high standards of data quality.
• Excellent communication and collaboration skills , with the ability to work effectively with cross-functional teams and stakeholders.