Data Engineer

Company Description Zaelot is a strategic partner for organizations undergoing digital transformation, specializing in Salesforce development, product development, and scalable engineering solutions. The company works with clients in Travel & Hospitality, Real Estate, Health, and News/Media, embedding world-class talent directly into client teams to accelerate delivery and create measurable impact. Zaelot is a people-first organization, focused on long-term partnerships, consistent delivery, and continuously raising the bar for quality. Transparency and open communication are core operating principles, enabling trust and clarity in every engagement. Engineers at Zaelot leverage advanced AI tools to reduce busy work and focus on meaningful technical and creative challenges that drive outcomes for partners.

Role Description This is a full-time remote role for a Data Engineer at Zaelot. The Data Engineer will design, build, and maintain scalable data pipelines to support analytics, reporting, and product features for client teams. Responsibilities include developing and optimizing ETL processes, modeling data structures, and implementing data warehousing solutions that ensure high data quality, performance, and reliability. The role involves collaborating closely with engineers, product managers, and business stakeholders to understand data needs, translate them into technical solutions, and continuously improve data infrastructure. The Data Engineer will also monitor data systems, troubleshoot issues, contribute to documentation, and adopt best practices in security, governance, and automation.

Qualifications

We are seeking a Data Engineer with a solid foundation in data engineering fundamentals and experience handling sensitive healthcare data.

• Hands-on experience building and maintaining data pipelines using Databricks (notebooks, jobs, and cluster configuration) and/or Snowflake (warehouses, virtual warehouse sizing, and workload management)
• Strong proficiency in SQL for querying, transforming, and validating data across multiple sources
• Practical experience designing and implementing ETL processes, from data extraction and transformation to loading into target systems
• Solid understanding of data pipeline architecture principles, including scalability, reliability, and maintainability of production workflows
• Working knowledge of HIPAA/PHI data governance and security compliance requirements, including safe handling, storage, and access control of protected health information
• Ability to troubleshoot and resolve data pipeline issues in a production environment
• Strong attention to detail and commitment to data quality and accuracy when working with sensitive datasets

Nice-to-have skills

• Experience with dbt for data transformation and modeling
• Familiarity with data governance tools (e.g., Microsoft Purview, Collibra)
• Experience with pipeline orchestration tools (Airflow, ADF, or similar)
• Exposure to cloud-native data platforms (Azure, AWS, or GCP)
• Experience with CI/CD for data pipelines