Senior Data Engineer (SAS to Databricks Migration)
NimbusAITech LLC
- Job
- 29292
- Posted
- Location
- Remote
- Work type
- Contract
- Tax terms
- W2, C2C, 1099
- Experience
- Experience open
- Rate
- $50 (Hourly)
- Openings
- 1 opening
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Skills
- SQL
- Python
- PySpark
- Spark
- Databricks
- Delta Lake
- Data Modeling
- SAS
- Azure
- CI/CD
About the job
Senior Data Engineer (SAS to Databricks Migration)
Location: Remote (USA)
Employment Type: Contract Role
Work Schedule: Flexible hours with core collaboration hours aligned to U.S. time zones
About the Role
Are you an experienced Data Engineer looking to make a massive impact in a remote setting? We are looking for a Senior Data Engineer with specialized expertise in migrating legacy systems to modern cloud architectures. In this role, you will lead the modernization of legacy workloads by migrating SAS-based processes to Databricks on Azure, delivering robust, high-performance data pipelines for advanced analytics and reporting.
Employment Type: Contract Role
Work Schedule: Flexible hours with core collaboration hours aligned to U.S. time zones
Key Responsibilities
Cloud Data Engineering: Design, build, and optimize scalable data pipelines on Azure utilizing Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Synapse, and Azure SQL.
Legacy Migration: Interpret, convert, and modernize legacy SAS workloads (including Base SAS and SAS macros) into modern, optimized Databricks environments.
Databricks & Spark Optimization: Leverage advanced Databricks capabilities, including Delta Lake and Apache Spark optimization, to enhance performance.
Query & Performance Tuning: Optimize the performance of complex Spark jobs and SQL queries.
Data Governance & Quality: Implement rigorous data quality, validation, and monitoring practices across all pipelines.
Version Control & CI/CD: Utilize Git and follow CI/CD best practices for seamless deployment and code management.
Required Qualifications
Experience: Minimum of 5+ years of hands-on data engineering experience.
Azure Expertise: Strong hands-on experience with Azure data services (ADF, ADLS, Synapse, Azure SQL).
Databricks & Spark: Advanced Databricks experience, including Delta Lake architecture and Spark optimization.
Programming: Proficiency in Python and PySpark.
SQL & Modeling: Expert-level SQL skills and solid experience with data modeling principles.
SAS Knowledge: Working knowledge of SAS (Base SAS, SAS macros) with a proven ability to interpret and translate legacy SAS code into modern frameworks.
Engineering Best Practices: Experience implementing data quality frameworks, monitoring practices, Git workflows, and CI/CD pipelines.