Data Engineer (SAS)

SUMMARY:
Data Engineer (SAS)
Contract
Remote

POSITION INFO:
Job Title: Data Engineer (SAS)

Location: Remote

About Our Client: Our client is a leading player in the insurance industry, dedicated to providing innovative solutions to meet the needs of our clients. They leverage cutting-edge technology to drive their business forward and are seeking a skilled Data Engineer to join their dynamic team. If you are passionate about data engineering and have a strong background in SAS, Spark, Databricks, and Python, we want to hear from you!

Job Description:
As a Data Engineer (SAS), you will play a crucial role in designing, developing, and maintaining our client's data infrastructure. You will work closely with cross-functional teams to ensure data is accessible, reliable, and valuable for business decision-making. This position requires a strong technical background, particularly in SAS, Spark, Databricks, and PySpark/Apache Spark, as well as a proven ability to handle complex data engineering tasks.

Key Responsibilities:

• Design, develop, and optimize data pipelines and ETL processes using SAS, Spark, and Databricks.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver high-quality data solutions.
• Implement and maintain robust data models and architectures to support analytics and reporting needs.
• Utilize PySpark/Apache Spark and Python API to process large volumes of data efficiently.
• Ensure data quality and integrity through rigorous testing, validation, and monitoring of data workflows.
• Continuously improve data engineering practices, tools, and methodologies to enhance team productivity and data reliability.
• Troubleshoot and resolve data-related issues, ensuring minimal disruption to business operations.
• Stay current with industry trends and emerging technologies to drive innovation within the data engineering function.

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or a related field.
• Intermediate to expert-level proficiency in SAS.
• Strong experience with Spark, Databricks, and PySpark/Apache Spark.
• Proficiency in Python and experience with Python API.
• Solid understanding of data warehousing concepts, ETL processes, and data modelling.
• Experience with big data technologies and frameworks.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.
• Experience in the insurance industry is a plus.

• Competitive salary and benefits package.
• Opportunity to work with a talented and passionate team.
• Professional development and growth opportunities.
• A collaborative and inclusive work environment.
• Flexible working arrangements.

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