Data Engineer

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We are seeking a Data Engineer to join our Data & Analytics team. This role is ideal for an early‑career engineer who is passionate about data, eager to learn modern cloud data platforms, and excited to grow within a collaborative data & analytics environment. In this role, you will support the development and maintenance of our data and analytics platform. You will work closely with other team members to help operate and modernize our data platform, contributing to both legacy systems (SQL Server) and our modern data stack built on Snowflake and dbt Cloud. The ideal candidate has a solid foundation in SQL, a working knowledge of Python, and a strong desire to learn modern ELT patterns, Snowflake-native capabilities, and analytics enablement tools.

Job Responsibilities:

Include but are not limited to

• Data Pipeline Support: Assist in building, maintaining, and monitoring ETL/ELT pipelines that ingest data from various source systems into Snowflake.
• Platform Operations: Support existing Informatica and SQL Server–based workflows, ensuring data pipelines run reliably, and issues are escalated appropriately.
• Modern Data Transformation: Contribute to dbt Cloud projects by developing and maintaining models, tests, and documentation.
• Snowflake Development: Create and optimize basic Snowflake SQL objects such as tables, views, and simple tasks while learning advanced Snowflake features.
• Collaboration: Work with Senior Data Engineers, Data Scientists, and Business Analysts to understand data requirements and translate them into well-structured datasets that support oil and gas operations.
• Learning & Growth: Actively participate in code reviews, team knowledge sharing, and training opportunities to build expertise in Snowflake, dbt, and modern data engineering practices.

Required Qualifications:

• Experience: 0–2 years of experience in data engineering, analytics engineering, or a related technical role (internships and co‑op experience welcome).
• Languages: Working knowledge of SQL. Basic to intermediate experience with Python for data processing or automation
• Databases & Data Platforms: Familiarity with relational databases (e.g., SQL Server, PostgreSQL, or similar). Exposure to cloud data platforms such as Snowflake is a plus
• Data Concepts: Understanding of core data engineering concepts such as ETL/ELT, data modeling, and data quality.
• Tools & Practices: Exposure to data transformation tools (dbt preferred). Comfort working with Git or another version control system. Experience with enterprise scheduling and orchestration tools (e.g., Automic) is a plus

Preferred Qualifications:

• Coursework or hands-on experience with Snowflake
• Exposure to dbt (Core or Cloud) through projects, labs, or professional experience
• Familiarity with Python data libraries (e.g., pandas)
• Interest in data visualization, analytics enablement, or self-service BI
• Curiosity about advanced analytics, machine learning, or AI-enabled data platforms

Diamondback is an Equal Employment Opportunity Employer. Diamondback provides equal employment opportunities to all qualified applicants without regard to race, sex, sexual orientation, gender identity, national origin, color, age, religion, veteran or disability status, genetic information, pregnancy, or any other status protected by law. Diamondback participates in E-Verify. Learn more about E-Verify .