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Job responsibilities:

Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
Develops secure high-quality production code, and reviews and debugs code written by others
Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Adds to team culture of diversity, equity, inclusion, and respect
Provides system administration support of Salesforce environment, especially related to customized applications, user permissions, security settings, custom objects and workflow

Required qualifications, capabilities, and skills:
Formal training or certification on data engineering concepts and 8+ years of applied experience
Advanced in one or more programming language(s), such as Java, Python
Hands-on practical experience delivering data pipelines
Proficient in all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies such as CI/CD, Applicant Resiliency, and Security
Demonstrated proficiency and experience with cloud-native distributed systems
Ability to develop reports, dashboards, and processes to continuously monitor data quality and integrity
Working knowledge of bitbucket and JIRA

Preferred qualifications, capabilities, and skills:
Hands-on experience building data pipelines on AWS using Lambda, SQS, SNS, Athena, Glue, EMR
Strong experience with distributed computing frameworks such as Apache Spark, specifically PySpark
Strong hands-on experience building event driven architecture using Kafka
Experience writing Splunk or Cloudwatch queries, DataDog metrics