Data Ops Engineer II

About Shamrock Trading Corporation

Shamrock Trading Corporation is a family of brands that has been serving the transportation and logistics industries since 1986. Shamrock offers factoring solutions, export financing, third‑party logistics, a fuel card program and trucking technology. Shamrock’s mission since the start has been to create value and success for our customers, our partners and our people. Strong ethics, dedication to our customers and close attention to the marketplace are critical to the success and growth of the Shamrock brands.

Shamrock is headquartered in Overland Park, Kansas, with multiple offices throughout the U.S. Overland Park is a great place to live, work and play, being conveniently located within driving distance of everything Kansas City has to offer. Housed within the heart of Overland Park, our offices include 4 gorgeous towers on the East and West sides of Metcalf Ave. With a heavy community presence and a winning culture, Shamrock is a great place to work in Overland Park!

Our award‑winning culture is a testament to our commitment to growth, recognition and empowerment. From day one, we prioritize employees first, encouraging them to think and act like owners and providing endless opportunities for growth and self‑development, both personally and professionally. Shamrock has been recognized as one of America’s 2025 “Most Loved Workplaces” by Newsweek.

• Training and Development:
  Ongoing training and professional development opportunities
• Medical:
  Fully paid healthcare, dental and vision premiums for employees and eligible dependents, and gym benefits
• Financial:
  Generous company 401(k) contributions and employee stock ownership after one year
• Work‑Life Balance:
  Competitive PTO and work from home opportunities after an introductory period

Shamrock Trading Corporation is seeking a Data Ops Engineer who is passionate about data automation and lifecycle management. As a pivotal member of our Data Services team, you will help implement cutting‑edge Data Ops methodologies to optimize our data engineering and analytics frameworks. Your work will ensure high‑quality data solutions and contribute to the overall robustness and reliability of our data systems.

• Develop and enhance Data Ops platforms and lifecycle processes, independently delivering complex automation and reliability improvements
• Develop, optimize, and maintain CI/CD pipelines for data workflows using Git Hub Actions, AWS Code Build/Code Deploy, or similar tools.
• Build and scale automated testing frameworks for data validation, schema checks, and regression testing
• Use a code-first approach to architect and implement data quality checks and monitoring solutions to ensure data accuracy and reliability
• Contribute to scalable data lake and data warehouse architectures using Databricks, Delta Lake, DABs, and modern data platform patterns
• Implement and improve monitoring and alerting using Prometheus, Cloud Watch, and Grafana.
• Enhance metadata management and data cataloging using Databricks Unity Catalog.
• Design and implement robust access controls and governance using AWS IAM, Unity Catalog, and Terraform, ensuring compliance with SOC 2 standards.
• Deploy, manage, and enhance scalability of infrastructure‑as‑code using Terraform and AWS services (S3, EKS, Lambda, ECS, IAM).
• Collaborate closely with engineering and analytics teams to ensure performance, scalability, cost‑efficiency, and identify operational risk in projects
• Provide tier 1 and 2 operational support for internal reporting and API requests, ensuring timely and secure data delivery
• Identify data anomalies and perform forensic analysis for conclusive RCA of data issues
• Communicate clearly during incidents and coordinate cross‑team problem solving.
• Participate in on‑call rotations while improving runbooks and reducing alert noise
• Independently perform proofs of concept (POCs) to validate solutions for operational issues and translate successful approaches into clear Jira stories for implementation
• Contribute to the evolution of Data Ops best practices, platform maturity, and team standards
• Create technical…