Principal Data Engineer

Benefits Overview

A career at CoBank can offer you the opportunity to make a personal impact on the people and communities where we do business. In order to be the best, we hire the best! Benefits Offered by CoBank:

• Careers with a purpose
• Time-Off Packages, 20 days of vacation, 10 paid sick days and 11 paid holidays
• Competitive Compensation & Incentive
• Hybrid work model: flexible arrangements for most positions
• Benefits Packages, including Medical, Dental and Vision coverage, Disability, AD&D, and Life Insurance
• Robust associate training and development with CoBank University
• Tuition reimbursement for higher education up to $10k per year
• Outstanding 401k: up to 6% matching and additional 3% non-elective contribution & Student Loan Match
• Community Impact: United Way Angel Day, Volunteer Day and Associate Directed Contribution
• Associate Resource Groups: creating a culture of respect and inclusion
• Recognize a fellow associate through our GEM awards

Job Description

CoBank is looking for a Principal Data Engineer to join our Data Engineering (DE) team which is responsible for building and maintaining our data lake, ingestion and consumption data pipelines / services and facilitating the movement of large data each day. We work directly with business teams and platform and engineering teams to ensure growth strategies at CoBank. You are an out-of-the-box, structured thinker who is passionate about building services that scale. You will play a key role in providing the end-to-end data engineering solutions to support key business initiatives As a Principal Data Engineer at CoBank, you will play a pivotal role in driving the design, development, and optimization of our data infrastructure and architecture. You will lead the implementation of complex data engineering solutions, leveraging cloud-native technologies, particularly AWS services and open-source software. You will collaborate closely with cross-functional teams to ensure the successful delivery of data-driven initiatives aligned with the organization's strategic objectives. Collaborate with and across Agile teams to design, develop, test, implement, and support data engineering solutions in full-stack development tools and technologies. Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, mentoring other members of the engineering community.

Essential Functions

• Lead the design and implementation of highly scalable data pipelines and ETL processes.
• Architect and optimize data storage and retrieval mechanisms, leveraging cloud-native solutions.
• Drive data governance, quality, and metadata management initiatives.
• Mentor junior engineers and promote innovation within the team.
• Communicate effectively with stakeholders at all levels to ensure alignment on data initiatives.

Education

• Bachelor's Degree in Computer Science, Information Technology, or related field. required
• Bachelor's degree may be substituted with four years of related experience (four years is in addition to what is minimally required for the role), or an equivalent combination of education and related experience.
• Master's Degree in Computer Science, Information Technology, or related field. preferred

Work Experience

• 8 years of relevant experience in data engineering, with a proven track record of designing and implementing scalable data solutions, required
• Prior Experience in a leadership or senior technical role within a data engineering team, required
• Prior Experience with cloud platforms, particularly AWS, and proficiency in leveraging AWS native services for data processing, storage, and analytics, required
• Prior Experience with other cloud platforms, such as Google Cloud Platform (GCP) or Microsoft Azure, preferred
• Prior Experience with on-premises development environments, preferred
• Prior Experience building self-service tooling and platforms, preferred
• Prior Experience building and design of Data Mesh architecture platforms preferred
• Expertise in designing and implementing complex data pipelines and ETL processes, preferably using cloud-native technologies.
• In-depth knowledge of data architecture principles, including data modeling, schema design, and optimization techniques.
• Proficiency in programming languages commonly used in data engineering, such as Python, Scala, or Java.
• Strong understanding of distributed computing frameworks and big data technologies, such as Apache Spark, Hadoop, or Flink.
• Excellent problem-solving and analytical skills, with th