Senior Data Engineer, Interviewer

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Sedona Digital

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

🔒 Cybersecurity

🤝 B2B

Artificial Intelligence • Cybersecurity • B2B

Sedona Digital is a process-led technology consultancy that helps enterprises define strategy, build AI- and data-driven products, modernise applications and secure and operate cloud-native environments. They offer services across technology strategy, data architecture and engineering, AI and predictive analytics, software product engineering, cloud migration and Azure managed services, DevOps/CICD, plus security and managed SOC capabilities to deliver ongoing operations and compliance.

📋 Description

• Conduct 60-minute technical interviews for Senior Data Engineer candidates. • Evaluate candidates' hands-on experience across modern data platforms and cloud-based data architectures. • Assess technical depth, engineering best practices, problem-solving ability, and real-world project experience. • Explore candidates' previous projects through detailed technical discussions and follow-up questions. • Evaluate knowledge of data engineering principles, cloud architecture, scalability, security, governance, and performance optimization. • Assess candidates' understanding of data lakes, lakehouses, data warehouses, and modern analytics platforms. • Assess communication skills and the ability to explain complex technical concepts clearly. • Complete structured interview scorecards and provide hiring recommendations after each interview. • Collaborate with recruiters to ensure consistent evaluation standards. • Contribute to improving interview questions and technical assessment processes when needed.

🎯 Requirements

• 8+ years of commercial experience as a Data Engineer. • Strong hands-on experience building and supporting data solutions on at least one major cloud platform (Azure, AWS, or GCP). • Strong understanding of modern data platform architectures, including Data Lakes, Lakehouses, Data Warehouses, and Analytics Platforms. • Extensive experience designing, building, and maintaining ETL/ELT pipelines. • Strong SQL skills and experience with data modelling, including facts, dimensions, star schemas, and semantic layers. • Experience with Python for data processing, automation, and orchestration. • Experience with distributed data processing technologies such as Apache Spark or equivalent frameworks. • Experience implementing secure authentication, authorization, and data security patterns within cloud environments. • Ability to evaluate both implementation details and high-level solution architecture. • Excellent spoken English. • Ability to conduct interviews professionally and provide objective candidate assessments.