Principal Data Engineer

Living Our Values: All associates are guided by Our Values, serving as the unifying foundation of our companies. We strive to ensure that every decision we make and every action we take demonstrates Our Values, creating lasting benefits for all associates, shareholders, and the communities in which we live.

Why Join Us: - **Career Growth:** Advance your career with opportunities for leadership and personal development. - **Culture of Excellence:** Be part of a supportive team that values your input and encourages innovation. - **Competitive Benefits:** Enjoy a comprehensive benefits package that looks after both your professional and personal needs.

Total Rewards: Our commitment to recognizing your contributions is reflected in our Total Rewards package. We offer a competitive compensation structure that includes base pay and performance-based rewards, determined by skill set, experience, qualifications, and job-related requirements. Our benefits include medical, dental, and vision insurance, wellness programs, retirement plans, and generous paid leave. Discover more about our offerings on our Benefits page.

A Day In The Life: As a Principal Data Engineer within the Data Science and Analytics team, you will play a crucial role in architecting, implementing, and managing robust, scalable data platforms. This position requires a blend of cloud data engineering, systems engineering, data integration, and machine learning systems knowledge to enhance GST's data capabilities, supporting advanced analytics, machine learning projects, and real-time data processing needs. You will guide team members and collaborate closely with cross-functional teams to design and implement modern data solutions that enable data-driven decision-making across the organization.

As a Principal Data Engineer, you will:

• Collaborate with Business and IT functional experts to gather requirements, perform gap analysis, and recommend/implement process or technology improvements to optimize data solutions.
• Design data solutions on Databricks, including Delta Lake, Data Warehouse, and Data Mart to support the organization's analytical needs.
• Implement scalable and reliable data pipelines for diverse data processing using technologies like Databricks, Apache Spark, Kafka, and AWS services (e.g., Glue, S3).
• Develop and optimize data models and storage solutions (SQL, NoSQL, Data Lakes) to support operational and analytical applications while ensuring data quality and accessibility.
• Utilize ETL tools and frameworks (e.g., Apache Airflow, Talend) to automate data workflows, and ensure timely data availability for analytics.
• Implement highly automated data workflows and deployment pipelines using tools such as Apache Airflow, Terraform, and CI/CD frameworks.
• Collaborate with data scientists and engineers, providing the required data infrastructure and tools for complex analytical models using programming languages like Python or Scala.
• Ensure compliance with data governance and security policies, implementing best practices in encryption and access controls.
• Establish best practices for code documentation, testing, and version control to ensure consistent data engineering practices.
• Monitor and troubleshoot data pipelines and databases for performance issues, optimizing access and throughput.
• Lead data projects, coach and mentor junior data engineers, and stay abreast of emerging technologies and methodologies in data engineering.

What We Need From You:

• Bachelor's Degree in Computer Science, Data Science, MIS, Engineering, Mathematics, Statistics, or a related discipline with 5-8 years of hands-on data engineering experience.
• Proven experience designing scalable and fault-tolerant data architectures and pipelines on Databricks and AWS.
• Deep experience with Databricks and AWS native data offerings, and solid experience with big data technologies (Databricks, Apache Spark, Kafka).
• Strong hands-on experience with ETL/ELT pipeline development using AWS tools, Databricks Workflows, and cloud services integration.
• Proficient in SQL and relevant programming languages (Python, Java, Scala); hands-on experience with RDBMS and data warehousing.
• Good understanding of system architecture and design patterns, with proficiency in Git and CI/CD pipelines.
• Familiarity with machine learning model deployment is a plus; experience with SAP, BW, HANA, Tableau, or Power BI is preferred.
• Strong understanding of project life-cycle and agile methodologies, with excellent communication skills for effective collaboration in a fast-paced environment.
• AWS Certified Solution Architect and/or Databricks Certified Associate Developer for Apache Spark are preferred certifications.

Physical and Environmental Requirements: The role requires daily analysis and interpretation of data, communication, and remaining stationary for significant periods, as well as moving about the office and occasionally lifting up to 25 pounds.

Travel Requirements: 20% travel to other sites, including out-of-state, may be required for business.

Join Us: The Friedkin Group and its affiliates are committed to ensuring equal employment opportunities, including reasonable accommodations for individuals with disabilities. If you require accommodation, please contact us at TalentAcquisition@friedkin.com. We celebrate diversity and are committed to creating an inclusive environment for all associates. We seek candidates legally authorized to work in the United States, without sponsorship.