DRC Systems
Overview
Cloud Data Engineer
at
DRC Systems
– Minneapolis, MN (Remote) Cloud Data Engineer with over 5 years of experience in managing structured and unstructured data, performing deep data analysis, and building scalable data pipelines. The ideal candidate has hands-on expertise in
Azure Data Factory
(ADF),
Snowflake ,
Databricks , and
Python/PySpark , with a strong understanding of cloud-based ETL processes and data normalization techniques. Key Responsibilities
Analyze and organize raw data from diverse sources, including healthcare datasets. Design and implement ETL pipelines using Azure Data Factory. Develop and optimize SQL queries, stored procedures, and data models in Snowflake. Parse and flatten semi-structured data (XML, JSON) using Snowflake and SQL. Build scalable data systems and pipelines to support analytics and reporting. Migrate on-premise data workloads to cloud platforms, preferably Snowflake. Work with Databricks using PySpark, SparkSQL, and Python for data transformation. Ensure data quality through profiling, validation, and adherence to governance standards. Collaborate in Agile development environments and contribute to continuous improvement. Identify opportunities to enhance data architecture and storage efficiency. Qualifications
5+ years of experience in data engineering or a related field. Hands-on expertise with Azure Data Factory (ADF), Snowflake, Databricks, and Python/PySpark. Strong knowledge of cloud-based ETL processes and data normalization techniques. Additional Information
We are not listing non-essential postings or salaries here. This posting focuses on the Cloud Data Engineer role and core requirements.
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Cloud Data Engineer
at
DRC Systems
– Minneapolis, MN (Remote) Cloud Data Engineer with over 5 years of experience in managing structured and unstructured data, performing deep data analysis, and building scalable data pipelines. The ideal candidate has hands-on expertise in
Azure Data Factory
(ADF),
Snowflake ,
Databricks , and
Python/PySpark , with a strong understanding of cloud-based ETL processes and data normalization techniques. Key Responsibilities
Analyze and organize raw data from diverse sources, including healthcare datasets. Design and implement ETL pipelines using Azure Data Factory. Develop and optimize SQL queries, stored procedures, and data models in Snowflake. Parse and flatten semi-structured data (XML, JSON) using Snowflake and SQL. Build scalable data systems and pipelines to support analytics and reporting. Migrate on-premise data workloads to cloud platforms, preferably Snowflake. Work with Databricks using PySpark, SparkSQL, and Python for data transformation. Ensure data quality through profiling, validation, and adherence to governance standards. Collaborate in Agile development environments and contribute to continuous improvement. Identify opportunities to enhance data architecture and storage efficiency. Qualifications
5+ years of experience in data engineering or a related field. Hands-on expertise with Azure Data Factory (ADF), Snowflake, Databricks, and Python/PySpark. Strong knowledge of cloud-based ETL processes and data normalization techniques. Additional Information
We are not listing non-essential postings or salaries here. This posting focuses on the Cloud Data Engineer role and core requirements.
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