Design and maintain scalable ETL/ELT pipelines in Azure and GCP using Azure Data Factory, Fabric, dbt, Fivetran, SSIS, and other solutions
Optimize and manage structured and unstructured data across SQL Server, Azure SQL, Data Lakes, and BigQuery
Lead the migration of data systems from IaaS (on-prem SQL Server) to PaaS/SaaS environments
Take ownership of the Power BI environment, including workspace administration, security, and capacity management
Build and maintain robust data models optimized for high-performance Power BI dashboards and SSRS reports
Implement enterprise-grade data security, privacy standards, and disaster recovery procedures
Proactively identify opportunities to automate workflows and reduce manual "toil"
Build comprehensive monitoring and alerting for data pipelines to minimize downtime and ensure data reliability
Maintain high-quality documentation of data lineage, system architectures, and process flows

5–10 years of professional data engineering experience, preferably within Financial Services or FinTech
Expert-level SQL optimization skills and proficiency in Python for scripting and data manipulation
Deep hands-on experience with SQL Server (DBA-level knowledge), SSIS, SSRS, Azure Data Factory, and Synapse
Familiarity with Google Cloud Platform (BigQuery) and modern transformation tools like dbt
Strong knowledge of Git-based workflows, CI/CD pipelines, and automated testing
Bachelor’s degree in Computer Science, Information Systems, or equivalent professional experience
Azure or GCP Data Engineering certifications (e.g., Azure Data Engineer Associate) are a significant plus
Must be located in or able to work consistently within the EST time zone (9:00 AM
5:00 PM)

Premium benefits plan fully paid by nesto, including comprehensive insurance
Unlimited access to telemedicine and mental health services for you and your family
4 weeks of vacation to ensure you stay at peak performance
Access to the resources and tech you need to execute without friction
Working framework that makes you productive and enables teamwork

Senior Data Engineer

Key skills