Senior Data Engineer I

C2FO•Kansas City, MO

3d•Remote

About The Position

We are looking for a talented and experienced Senior Data Engineer I to join our growing data ingestion team. In this role, you will collaborate with data scientists, analysts, marketing, sales, and application developers to design, develop, and maintain scalable data systems and pipelines that power critical business insights. This is an exciting opportunity to work in a fast-paced environment and have a significant impact on our data infrastructure.

Requirements

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience).
5+ years of experience in data engineering, with a proven track record of solving complex problems and scaling data pipelines.
Strong SQL skills and experience with data processing frameworks (e.g., Apache Spark, Apache Kafka).
Expertise in cloud data platforms (AWS).
Proficiency in Python, Java, or Scala.
Experience with AWS Glue.
Solid understanding of data warehousing concepts (e.g., Redshift).
Strong analytical and problem-solving skills, with the ability to work independently and exercise good judgment.

Nice To Haves

Hands-on experience with ETL tools like Airflow.
Experience with DBT(data build tool).
Experience with data modeling, governance, and quality assurance.
Experience in software application development.
Experience with containerization and orchestration tools (Docker, Kubernetes).
Familiarity with machine learning workflows and model deployment pipelines.
Power BI management and report building.
Knowledge of data security best practices and frameworks.

Responsibilities

Solve Complex Problems: Apply your broad experience and expertise to develop innovative solutions for complex data challenges. Use professional judgment to determine the best methods and techniques for problem-solving, even in unfamiliar territory.
Data Architecture & Engineering: Design, develop, and maintain high-performance, scalable, and testable data pipelines and ETL processes.
Cross-Functional Collaboration: Partner with data science, analytics, product, marketing, and engineering teams to translate business needs into scalable data solutions. Network with senior internal and external stakeholders to enhance data strategies.
Autonomy & Ownership: Work with minimal oversight, ensuring technical integrity in all solutions. Define methods and procedures for new assignments and contribute to the coordination of data engineering activities.
Optimize & Maintain Data Infrastructure: Ensure system performance, reliability, and security by continuously improving existing data platforms.
Data Governance & Quality: Implement and advocate for best practices in data governance, security, and quality assurance.
Leadership & Mentorship: Influence project planning and timelines, provide actionable feedback, and mentor junior engineers to foster a high-performing, collaborative team.
Stay Ahead of Industry Trends: Keep up with emerging technologies and best practices to continuously improve data engineering processes.