We are seeking a talented and experienced Data Engineer cum SAS Consultant to join our team. The ideal candidate will possess a strong background in data engineering, SAS programming, and proficiency in Python and Spark or PySpark. The role involves designing, developing, and implementing data solutions while leveraging SAS tools to provide insightful analytics. The candidate should have a passion for data, strong problem-solving skills, and the ability to work collaboratively in a dynamic environment.
Key Responsibilities:
- Data Engineering:
- Design, develop, and maintain scalable and efficient data pipelines for large volumes of structured and unstructured data.
- Collaborate with cross-functional teams to understand data requirements and implement solutions that meet business needs.
- Utilize SAS programming skills to extract, transform, and load (ETL) data for analytical purposes.
- Develop and implement SAS solutions for data manipulation, statistical analysis, and reporting.
- Provide expertise in SAS programming to support analytics and business intelligence initiatives.
- Proficient in Python for data manipulation, analysis, and automation.
- Experience with Spark or PySpark for distributed data processing and analytics.
- Perform exploratory data analysis to identify trends, patterns, and anomalies in the data.
- Collaborate with data scientists and analysts to deliver actionable insights from complex datasets.
- Implement data quality checks and ensure the accuracy and reliability of data used in analytical processes.
- Troubleshoot and resolve data-related issues in a timely manner.
- Create and maintain comprehensive documentation for data pipelines, SAS programs, and analytical processes.
- Work closely with business stakeholders, data scientists, and other team members to understand requirements and deliver effective data solutions.
- Bachelor's or Master’s degree in Computer Science, Data Science, or a related field.
- Proven experience as a Data Engineer with a focus on SAS programming.
- Strong proficiency in Python and experience with Spark or PySpark.
- Solid understanding of data modeling, ETL processes, and data warehousing concepts.
- Excellent problem-solving and analytical skills.
- Effective communication and collaboration skills.
- SAS certification is a plus.
