Data Engineering Professional

At Devon, we will offer you a career full of energy and unmatched opportunities to solve today’s greatest challenges. Innovation, creative problem-solving and positive change happen when people step out of their comfort zone and think differently. Our values, workplace practices, wellness programs, benefits and compensation are aimed at helping employees manage their unique personal life and care for their families so they can focus on contributing to the fullest.

The Senior Data Engineering Professional, working under limited supervision, is responsible for designing, developing, and maintaining robust data pipelines to facilitate efficient and reliable data movement across systems while ensuring data integrity and optimal performance within Devon’s Data Hub. The role designs and implements data processing systems using cutting-edge technologies such as Databricks, PySpark, Snowflake, Azure DevOps, and Tidal to provide timely insights for business operations. The role contributes to strategic data planning, offering insights into emerging technologies and industry trends. The role collaborates with cross-functional teams to understand data requirements and provides support for advanced analytics and machine learning, with a preference for experience in AI. The role implements scaling strategies for data systems, optimizing performance, and ensuring data security compliance.

- Designs, codes, tests, debugs, and documents data applications/programs, working with junior developers to ensure that code is written in a testable way and designs efficient processes that can scale as required by stakeholders.

- Recommends code improvement opportunities for readability, testability, and efficiency, and designs tests that ensure expected output in complex situations.

- Designs and implements data processing systems, leveraging latest technologies such as Databricks, PySpark, and Snowflake to enable timely and actionable insights for business operations and decision-making.

- Refines the organization's data architecture, introducing advanced concepts such as data lakes, data mesh, and event-driven architectures to support evolving business requirements and data ecosystem complexity.

- Contributes to strategic data planning by providing insights into emerging technologies, industry trends, and best practices, guiding the organization in making informed decisions about future data investments.

- Collaborates with cross-functional teams, including data science, engineering, and business intelligence, to understand overarching business goals and provides data-driven solutions that drive value across the organization.

- Stays abreast of the latest advancements in data engineering, cloud and AI Technologies, and fosters a culture of continuous learning within the team to maintain technical excellence.

- Implements strategies for horizontal and vertical scaling of data systems, continuously optimizing performance and resource utilization to accommodate growing data volumes and evolving business requirements.

- Works under limited supervision, selects appropriate data platform(s) for the specific use case, leads concurrent projects, mentors less-experienced professionals, and initiates change, driving improvements within the data engineering discipline.

- Cultivates effective relationships, shares knowledge, and provides influence over data engineering projects and peer groups, demonstrating understanding of industry best practices.

- Identifies, diagnoses, and recommends solutions independently, collaborates across disciplines, and demonstrates advanced data engineering project management skills, contributing to company performance and goals.

Education

- Bachelor's Degree in Information Technology, Computer Science, or any other related discipline and/or commensurate work experience is required.

Experience

- 5+ years of relevant experience, preferably in Information Technology specializing in areas such as Data Architecture, Data Integration, Data Warehousing, Data Quality and Governance, or a related field. Industry experience is preferred.

Competencies

- Stakeholder Relationships

- Oral & Written Communication

- Results Oriented

- Active Learning

- Digital Literacy

Skills

- Data Architecture

- Data Modeling

- Data Integration

- Data Quality

- Data Processing

- Scripting

- Cloud Computing

- Structured Query Language (SQL)

- Risk Analysis

- Testing

- Experience with Databricks, PySpark, Snowflake, Azure DevOps, Tidal

- AI and Machine Learning (preferred)

Qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, status as a protected veteran or other characteristics protected by law.

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