Rush University Medical Center
Location: Chicago, Illinois
Pay: $46.07/hr – $68.64/hr
Overview The Data Engineer is responsible for designing and implementing data pipelines for cloud projects. This position will require working with complex data sources and transforming it into something useful for analysts. The role exemplifies Rush’s mission, vision and values and acts in accordance with Rush policies and procedures.
Responsibilities
Design, develop, and maintain data pipelines to enable data analysis and reporting.
Build, evolve, and scale infrastructure to ingest, process, and extract meaning out of data.
Write complex SQL queries or Python code to support analytics needs.
Manage projects/processes, working independently with limited supervision.
Work with structured and unstructured data from a variety of data stores, such as data lakes, relational databases, and/or data warehouses.
Combine, optimize, and manage multiple big data sources.
Build data infrastructure and determine proper data formats to ensure data is ready for use.
Qualifications
Bachelor’s Degree.
5 years of experience in data engineering, cloud computing, software engineering, and data processing.
Strong background in cloud computing, ETL tools such as Pentaho, Talend, Informatica, Azure Data Factory, Apache Kafka, and Apache Camel.
Experience designing and implementing analytical solutions on Hadoop-based platforms such as Cloudera, Hortonworks, or Spark-based platforms such as Databricks.
Proficient in RDBMS such as Oracle, SQL Server, DB2, MySQL, etc.
Strong analytical and problem‑solving skills.
Strong verbal and written communication skills.
Proficient programming skills in Python, SQL, NoSQL, and Spark.
Ability to manage multiple projects, work independently or in groups, prioritize time, and adapt to a rapidly changing environment.
Preferred Qualifications
Cloud certifications in AWS, Azure, or GCP.
Rush is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics.
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Pay: $46.07/hr – $68.64/hr
Overview The Data Engineer is responsible for designing and implementing data pipelines for cloud projects. This position will require working with complex data sources and transforming it into something useful for analysts. The role exemplifies Rush’s mission, vision and values and acts in accordance with Rush policies and procedures.
Responsibilities
Design, develop, and maintain data pipelines to enable data analysis and reporting.
Build, evolve, and scale infrastructure to ingest, process, and extract meaning out of data.
Write complex SQL queries or Python code to support analytics needs.
Manage projects/processes, working independently with limited supervision.
Work with structured and unstructured data from a variety of data stores, such as data lakes, relational databases, and/or data warehouses.
Combine, optimize, and manage multiple big data sources.
Build data infrastructure and determine proper data formats to ensure data is ready for use.
Qualifications
Bachelor’s Degree.
5 years of experience in data engineering, cloud computing, software engineering, and data processing.
Strong background in cloud computing, ETL tools such as Pentaho, Talend, Informatica, Azure Data Factory, Apache Kafka, and Apache Camel.
Experience designing and implementing analytical solutions on Hadoop-based platforms such as Cloudera, Hortonworks, or Spark-based platforms such as Databricks.
Proficient in RDBMS such as Oracle, SQL Server, DB2, MySQL, etc.
Strong analytical and problem‑solving skills.
Strong verbal and written communication skills.
Proficient programming skills in Python, SQL, NoSQL, and Spark.
Ability to manage multiple projects, work independently or in groups, prioritize time, and adapt to a rapidly changing environment.
Preferred Qualifications
Cloud certifications in AWS, Azure, or GCP.
Rush is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics.
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