Job Summary

Job Description

DUTIES:                            Contribute to a team responsible for performing data engineering in an AWS cloud environment using S3, RDS, Lambda, CloudWatch, and Secrets Manager; perform SQL CRUD operations; use joins, aggregations, and window functions in SQL; work with the following categories of SQL commands: DDL, DML, DCL, DQL, and TCL; use MS Office Suite, including Excel for tabular data manipulation, PowerPoint for delivering presentations, Word for documentation, Outlook for emails, OneNote for note taking and management, and Loop for planning, collaboration, and information sharing; develop and consume APIs; perform ETL processes on data using Python, PySpark, and Spark; perform code version control using GitHub; use JIRA for task and backlog management; use Aha for feature management; use ServiceNow for Change and Incident Management; use Confluence for documentation; develop software using the following: Dynamics365 or Salesforce, MuleSoft (for API management), Windows Server, and GitHub CoPilot (for code); use MS SQL Server and SQL Server Integration Services (SSIS); work in a DevOps environment; manage data platforms and infrastructure using Terraform; build CI/CD pipelines using Concourse; work with Scaled Agile Framework (SAFe); build CI/CD pipelines across data domains including Measurement and Attribution, Customer, Audience, and Finance; provide production support for existing data applications, ensuring proactive monitoring and data quality in Monte Carlo, and ensuring that SLAs are being met; contribute toward the design and delivery of data solutions, including requirement gathering, testing and evaluation of plans, and producing technical documentation; troubleshoot data pipeline issues and coordinate data anomalies across teams; manage pipeline changes and workflow enhancements with automated deployment tools; and track and evaluate performance metrics of pipeline or platforms, and implement cost-efficient optimizations. Position is eligible for 100% remote work.

REQUIREMENTS:            Bachelor’s degree, or foreign equivalent, in Computer Science, Engineering, or related technical field, and two (2) years of experience performing data engineering in an AWS cloud environment using S3, RDS, Lambda, CloudWatch, and Secrets Manager; performing SQL CRUD operations; using joins, aggregations, and window functions in SQL; working with the following categories of SQL commands: DDL, DML, DCL, DQL, and TCL; using MS Office Suite, including Excel for tabular data manipulation, PowerPoint for delivering presentations, Word for documentation, Outlook for emails, OneNote for note taking and management, and Loop for planning, collaboration, and information sharing; developing and consuming APIs; performing ETL processes on data using Python, PySpark, and Spark; performing code version control using GitHub; using JIRA for task and backlog management; using Aha for feature management; using ServiceNow for Change and Incident Management; using Confluence for documentation; of which one (1) year includes developing software using the following: Dynamics365 or Salesforce (or any other equivalent CRM), MuleSoft (for API management), Windows Server, and GitHub CoPilot (for code); using MS SQL Server and SQL Server Integration Services (SSIS); working in a DevOps environment; managing data platforms and infrastructure using Terraform; building CI/CD pipelines using Concourse; and working with Scaled Agile Framework (SAFe).

Disclaimer: This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.

Skills

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