Senior Data Analytics and Operations Engineer

<div class="content-intro"><p>The key to our success is simple; we deliver the highest quality, on time, with passion and commitment, and live every day by a set of great values. We've built a company that fosters long-term careers in an environment of continuous learning, with cutting-edge benefits, tools, and resources. In addition, certifications that endorse our company as a great place to work.</p> <p> </p></div><h3><strong>Responsibilities</strong></h3> <p></p> <ul> <li>Monitor and support daily ELT pipelines and reporting processes.</li> <li>Design, document, and maintain data warehouse models as source systems evolve. </li> <li>Develop and maintain semantic-layer and business intelligence data models. </li> <li>Support month-end reporting and recurring business processes. </li> <li>Improve and prepare data assets for AI-enabled workflows and automation initiatives. </li> <li>Design data transformations to improve data quality, consistency, accessibility, and usability. </li> <li>Troubleshoot data issues and support analytics requests across the organization. </li> <li>Serve as the primary technical resource for analytics infrastructure and reporting systems. </li> <li>Prepare internal metrics, analytics, and leadership reporting. </li> <li>Collaborate with stakeholders on data-driven initiatives and continuous improvements. </li> </ul> <p></p> <h3>Requirements</h3> <p></p> <ul> <li>6+ years of professional experience in analytics engineering, data engineering, business intelligence, analytics, or related fields</li> <li>Proven experience owning analytics and data infrastructure end-to-end, including the ability to make technical and architectural decisions independently.</li> <li>Demonstrated ability to operate with a high degree of autonomy and self-sufficiency, identifying problems, defining solutions, and executing them without requiring constant guidance.</li> <li>Strong understanding of data warehousing, dimensional modeling, semantic-layer concepts, and modern analytics architectures.</li> <li>Extensive experience designing, building, maintaining, and troubleshooting ELT/ETL pipelines in production environments.</li> <li>Advanced SQL and data modeling skills, including experience working with complex transformations and business logic.</li> <li>Strong hands-on professional experience with <strong>dbt, Amazon Redshift, Amazon QuickSight, AWS, Python, Docker, GitHub, and SQL</strong>.</li> <li>Experience maintaining and evolving existing data platforms, including legacy data cleanup, data reconciliation, and complex financial or business logic.</li> <li>Strong problem-solving and troubleshooting skills, with the ability to independently investigate ambiguous data, pipeline, reporting, or infrastructure issues.</li> <li>Startup mindset: proactive, adaptable, resourceful, and comfortable working in environments where priorities, systems, and requirements evolve quickly.</li> <li>Strong communication, documentation, and stakeholder management skills, including the ability to translate business requirements into scalable technical solutions.</li> <li>Advanced English.</li> </ul> <div> </div> <div><strong>Nice to Have</strong></div> <ul> <li>Experience designing or building analytics infrastructure from the ground up.</li> <li>Experience with CI/CD workflows for analytics or data engineering systems.</li> <li>Experience improving data quality, observability, governance, and reliability across co