All About You:
• Experience as a Data Engineer or in a similar role, with strong knowledge of data engineering concepts, methodologies, and modern data architectures.
• Strong hands-on experience with SQL, including writing and optimizing queries for large-scale data processing.
• Strong experience with relational databases, particularly Microsoft SQL Server and related technologies.
• Experience designing, implementing, and maintaining ETL/ELT pipelines and data integration solutions.
• Strong experience with distributed data processing and large-scale data platforms; experience with Databricks and Spark is a plus.
• Experience building and maintaining data lakes, data models, and scalable database solutions for analytics and reporting.
• Knowledge of workflow orchestration and automated end-to-end data pipelines.
• Understanding of data security, governance, compliance, and data quality practices, particularly in enterprise environments.
• Experience with cloud platforms such as AWS, Azure, or GCP and modern data engineering tools.
• Experience with event-driven or streaming architectures and exposure to machine learning or advanced analytics environments is a plus.
• Strong troubleshooting, root cause analysis, critical thinking, and problem-solving skills, with the ability to break down complex technical challenges.
• Ability to manage multiple projects and competing priorities while maintaining high standards for quality, accuracy, and delivery.
• Strong verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Self-motivated and collaborative team player with the ability to influence technical decisions, mentor engineers, and demonstrate curiosity about emerging technologies and developer productivity tools such as GitHub Copilot.
• Bachelor’s degree in a quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field. Equivalent practical experience may also be considered.