Sr. Data Engineer

Summary:

CommunityAmerica Credit Union is seeking a strong and experienced Senior Data Engineer as part of its Data Platform team to build scalable enterprise data solutions that drive strategic business outcomes. The goal of the Data Platform Team is to execute on a data and analytics strategy that enable personalized member experience and help achieve CommunityAmerica’s membership growth, engagement, and well-being strategic goals.

You will be responsible for developing and maintaining data pipelines and data in our data warehouse to support Data Science, Business Intelligence and business operations.

Duties & Responsibilities:

• Work with Product Owners to understand and translate business requirements into technical specifications and logical & physical data model requirements.
• Build, implement and test data pipelines using Databricks, Azure Data Factory, SSIS and other data integration tools.
• Support team members with troubleshooting and resolving complex technical issues and challenges.
• Follow proper coding standards, conduct code reviews to ensure proper code quality level.
• Follow effective source code management and CI/CD best practices to ensure data pipelines are automatically tested, integrated and deployed to production.
• Contribute to continuously improve existing data architecture and frameworks.
• Assist in the development and implementation of data governance and management solutions.
• Stay abreast with evolution of cloud Data technologies, frameworks, and best practices to continuously evolve CommunityAmerica’s Data platform and solutions.
• Promotes honest and open communication throughout the credit union.
• Demonstrate behaviors that are consistent with the credit union’s values, philosophies, and leadership characteristics.

Requirements:

Education and Experience Requirements:

• Bachelor’s Degree or higher in Computer Science, Engineering, or related field required.
• 8+ years of experience in data engineering and data warehousing.
• 5+ years of cloud data engineering and big data experience.
• 5+ years of data engineering experience in SSIS and/or other data integration technologies.
• 3+ years with building/using cloud data warehouse and data marts.

Required Knowledge, Skills and Abilities:

• Experience with cloud data engineering and data warehouse technologies in Microsoft Azure, Google or AWS. Experience in Azure is highly preferred.
• Strong programming skills in python and SQL for data processing and automation.
• Strong technical skills in big data and Data integration technologies including Spark, Kafka, Databricks, Azure Data Factory, SSIS and SQL.
• Development experience in Microsoft SQLServer including experience with tuning queries to optimize performance.
• Skilled in Visual Studio with the use of source control applications such as Azure DevOps.
• Experience with CI/CD and Jenkins.
• Experience with delivering data solutions iteratively using the Agile Scrum framework and development processes.
• Demonstrated ability to troubleshoot and resolve complex technical issues related to data processing in a cloud big data infrastructure.
• Exceptional analytical and conceptual thinking skills coupled with strong written and verbal communication skills.
• Passion for solving business problems through using data and creating analytical solutions.
• Excellent interpersonal skills, with the ability to effectively collaborate with cross-functional teams, stakeholders, and senior management.
• Able to communicate effectively, both written and orally, with internal and external customers, vendors, and partners.
• Ability to interact effectively with co-workers to accomplish daily tasks and to resolve interpersonal conflicts and miscommunications.
• Thrives in ambiguous technology situations.

Preferred Knowledge, Skills and Abilities:

• Financial industry knowledge.
• Development experience with Power BI and SSRS/Power BI Paginated reports.
• Experience with Lake house architecture.
• Experience in data modeling for transactional and analytical needs. Experience with NoSQL databases is preferred.