Job description

Our client is looking for a mid-level Data Engineer to assist in the design, build and maintenance of their cloud environment. Key Responsibilities: Primary Responsibilities Data Engineering (80%) • Design, build, and maintain robust, scalable data pipelines using Databricks on cloud platforms (e.g., Azure or AWS). • Develop and manage data models that support analytics, reporting, and operational use cases. • Implement best practices for data lake architecture, ensuring high availability, performance, and data quality. • Collaborate with analysts, data scientists, and business stakeholders to understand data requirements and deliver high-impact solutions. • Automate data ingestion, transformation, and loading processes (ETL/ELT) using modern orchestration tools. • Optimize and monitor pipeline performance and troubleshoot data-related issues proactively. • Ensure compliance with data governance and security standards. Secondary Responsibilities Cloud Data Environment Support (20%) • Support the ongoing operations and enhancements of the organizations Cloud Data Environment. • Assist with user onboarding, environment monitoring, and issue resolution. • Collaborate with IT and cloud teams to ensure optimal integration and performance. • Contribute to documentation, training, and knowledge-sharing related to the cloud data environment. Qualifications: • Bachelors or Masters degree in Computer Science, Engineering, Data Science, or a related field. • 3+ years of experience in a data engineering or similar role. • Proficiency with Databricks, Spark, and cloud data platforms (e.g., Azure Data Lake, AWS S3). • Strong SQL and Python skills. • Experience with data modeling, ETL/ELT pipeline design, and workflow orchestration tools (e.g., Airflow, dbt). • Familiarity with data governance, security, and performance optimization. • Experience supporting enterprise cloud data environments is a plus.

Requirements