Senior Data Engineer

5+ years of experience in data engineering and ELT with a focus on large-scale data platforms 3+ years of experience with Databricks Advanced proficiency in analytical SQL, including ANSI SQL, T-SQL, and Spark SQL Strong Python skills for data engineering Expertise in data modeling Hands-on experience with data quality and observability practices Practical knowledge of orchestration tools and CI/CD concepts for data workflows Excellent communication and a track record of technical leadership and mentoring Strong understanding of integrating data solutions with AI and machine learning models Strong problem-solving skills and attention to detail. Experience with version control systems like Git preferred Strong understanding of data governance and best practices in data management, with hands-on experience using Unity Catalog Hands-on experience in designing and managing data pipelines using Delta Live Tables (DLT) on Databricks Streaming and ingestion tools, such as Kafka, Kinesis, Event Hubs, Debezium, or Fivetran DAX, LookML, dbt; Airflow/Dagster/Prefect, Terraform; Azure DevOps; Power BI/Looker/Tableau; GitHub CoPilot knowledge is a plus Bachelor’s degree in Computer Science, Information Technology, or a related field. Master’s degree preferred

Design, develop, and maintain a scalable data warehouse/lakehouse environment. Design and implement ELT pipelines for data ingestion, transformation, and delivery. Ensure data security and compliance, including role-based access controls and encryption. Optimize performance of data workflows and storage for cost efficiency and speed. Partner with engineers, analysts, and stakeholders to meet data needs. Define and implement robust testing frameworks, enforce data contracts, and establish observability practices. Monitor, troubleshoot, and resolve data & automation issues. Collaborate within an Agile-Scrum framework and develop technical design documentation. Serve as a trusted expert on organizational data domains, processes, and best practices.