What are the responsibilities and job description for the Sr Data Engineer position at H&R Block?
JOB SUMMARY
Maintain End-to-End Cloud Infrastructure and Security. Design, build, test and maintain data pipelines and data warehouses (Enterprise Data warehouse and Data Lake design). Deliver Cloud infrastructure strategies with a focus on Cloud migrations and deployments. Design, implement, and support infrastructure automation. Guide Onshore/Offshore developers to build/scale data pipelines. Provide data solutions, build Enterprise Data Warehouse, and manage Enterprise data to implement critical project tasks, enhancements, and production issues. Ensure code quality through mechanisms including code coverage, peer reviews, and pair programming. Create and maintain CI/CD pipelines for code deployment. Extract data (encrypted). Lead efforts to transform raw and disparate data sets into inputs for computational analytics efforts. Design and develop scalable ETL packages. Implement statistical data quality procedures on new data sources, and apply iterative data analytics. Analyze and extract information from large amounts of data to create novel ML approaches. Build machine-learning models. Test, validate and deploy Machine Learning and Optimization models.
QUALIFICATIONS
Bachelor’s degree in Computer Science, Computer Information Systems, Information Technology, or a related field.
Five years of experience developing software solutions to include:
One year of which must include:
In lieu of a Bachelor’s plus 5/1 years of experience, a Master’s plus 3/1 years is acceptable.
Maintain End-to-End Cloud Infrastructure and Security. Design, build, test and maintain data pipelines and data warehouses (Enterprise Data warehouse and Data Lake design). Deliver Cloud infrastructure strategies with a focus on Cloud migrations and deployments. Design, implement, and support infrastructure automation. Guide Onshore/Offshore developers to build/scale data pipelines. Provide data solutions, build Enterprise Data Warehouse, and manage Enterprise data to implement critical project tasks, enhancements, and production issues. Ensure code quality through mechanisms including code coverage, peer reviews, and pair programming. Create and maintain CI/CD pipelines for code deployment. Extract data (encrypted). Lead efforts to transform raw and disparate data sets into inputs for computational analytics efforts. Design and develop scalable ETL packages. Implement statistical data quality procedures on new data sources, and apply iterative data analytics. Analyze and extract information from large amounts of data to create novel ML approaches. Build machine-learning models. Test, validate and deploy Machine Learning and Optimization models.
QUALIFICATIONS
Bachelor’s degree in Computer Science, Computer Information Systems, Information Technology, or a related field.
Five years of experience developing software solutions to include:
- MySQL and RDBMS.
- Data warehouse and ETL solutions.
- Microservices architecture and REST APIs.
- Big-data technologies.
- Hadoop stack: HDFS, Yarn, Hive, Spark, Kafka, HBase, Zookeeper, RStudio, Scala programming, and H2O.
- Server-side programming using J2EE technologies.
- Python, Perl, JavaScript, R, Shiny, Shell.
- CI/CD pipelines, PowerShell, and NoSQL.
- Data Encryption.
One year of which must include:
- Azure technology: Azure DevOps, Azure services, Azure Data Factory, Azure Databricks, ADLS/Blob, and Azure Function.
- Cloud data migration to infrastructure as a service (IaaS) or platform as a service (PaaS).
- Impala, Hue, and Kerberos.
In lieu of a Bachelor’s plus 5/1 years of experience, a Master’s plus 3/1 years is acceptable.
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