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.