Senior Data Engineer

Why should you join our team?

American AgCredit offers a unique opportunity to be a part of a national financial system supporting those who feed, clothe and fuel the world. We are a growing organization embracing collaboration and innovation while delivering transformative solutions. American AgCredit provides a cultivating environment where you truly make a difference for our customers and teams.

Benefits offered by American AgCredit:

• Commitment to agriculture and the communities we serve
• Family friendly work environment
• Investment in employee development
• Medical, Dental and Vision coverage
• Outstanding 401k – automatic 3% employer contribution, plus match up to 6%
• Generous Paid Time Off (Vacation accrued at 21 days annually, Sick Days accrued at 15 days annually, 12 paid holidays, plus 16 hours of volunteer time)
• Competitive Incentive Compensation Plan
• Disability & Life Insurance
• Employee mental, physical, and financial wellness programs
• The position is bonus eligible based on association and personal performance

Position will be posted until filled.

BASIC FUNCTION:

As part of the Data Capability Development Group within Customer Enablement, the Data Engineer is responsible for development and maintenance of the Association’s core data platforms, building data assets and pipelines in a combination of modern cloud-native and hosted data warehouse environments.

The Developer designs and implements software and systems that provide timely, accurate, and meaningful enterprise data to key consumers and decision makers in the Association so they can effectively analyze business patterns and trends and make informed decisions.

ESSENTIAL DUTIES:

• Be involved in all phases of the development life cycle as an individual contributor adhering to Association’s standards and best practices.

• Understand Agile development concepts and incorporate regular end-user feedback into design and prototypes.

• Create and maintain clear and concise technical specifications and documentation.

• Design, implement, and maintain data warehouse(s) in a cloud environment such as Snowflake.

• Design, implement, and maintain near real-time and batch data pipelines via practical application of existing and new data engineering techniques.

• Develop continuous integration and continuous deployment pipelines for data solutions that include automated unit & integration testing.

• Using ETL/ELT tools, transform/load data from source systems to target data models that will be used for system integration and analytics use cases.

• Build and maintain data ingestion and validation pipelines for both structured and unstructured data sources to ingest, transform, and aggregate data from disparate sources based on business requirements.

• Build semantic/abstraction layer views with a data virtualization tool such as Denodo.

• Work collaboratively with other analysts, engineers, data architects, data scientists, analytics teams, and business product owners in an agile environment.

• Help define and follow best practices in data engineering, data pipeline patterns, and framework-driven development.

• Perform other functions as assigned.

LEVELS OF SUPERVISION EXERCISED AND RECEIVED:

Exercises no supervision; regularly provides technical guidance and training; makes independent decisions; works under general direction.

TYPICAL EDUCATION AND EXPERIENCE:

• BS in Computer Science or a related field and/or equivalent technical competency.

• Minimum 7 years of software development and design with demonstrated proficiency in Data development such as ETL, pipelines, virtualization views, etc.

• Experience and/or understanding in the design and build of data models.

• Knowledge of relational and dimensional data design principles and practices.

• Experience and solid understanding of Extract Transform Load (ETL) tools and Data Warehousing preferably in a cloud-native environment.

• Understanding of the software lifecycle and software engineering best practices, including specification, documentation, configuration management, testing and quality assurance.

• Experience and/or knowledge in building data lakes, cloud data platforms leveraging cloud native architecture (Snowflake/Azure), ETL/ELT (Matillion/ADF), Replication (Fivetran/DBT), and data virtualization (Denodo).

• Familiarity with columnar, NoSQL database technologies and languages such as Python and Java.

• Experience with version control (i.e., Subversion), issue tracking and bu