Data Engineer

Owns the end-to-end data architecture across both AWS and Azure — from storage and ingestion patterns to governance and security. Works closely with engineering leads and business stakeholders to define a target-state architecture and evaluate the tools and services that support it, and provides architectural oversight as the platform is built out.

Key Responsibilities:

• Define and own the target-state data architecture across AWS and Azure environments
• Design data lake / data warehouse solutions, including storage layers, ingestion patterns, and processing frameworks
• Establish data governance, security, and access-control standards across both cloud platforms
• Translate business requirements into scalable, well-documented technical designs
• Evaluate and select tools/services across AWS and Azure, balancing cost, performance, and maintainability
• Provide architectural guidance and review to engineering teams during implementation
• Support cloud migration and multi-cloud integration initiatives

Requirements:

• 8+ years in data architecture/engineering, including senior/lead-level design responsibility
• Hands-on architecture experience with both AWS (S3, Redshift, Glue, Lake Formation, Athena) and Azure (ADLS, Synapse, Data Factory, Databricks)
• Proven track record designing large-scale data lakes/warehouses and enterprise data governance frameworks
• Strong grasp of data modeling, ETL/ELT design, and distributed data processing (Spark)
• Experience with data security, compliance, and access management across cloud platforms
• Track record leading multi-cloud or cloud-migration data initiatives
• Excellent stakeholder communication; able to present architecture decisions to technical and business audiences

Nice to Have:

• Cloud certifications (AWS Certified Solutions Architect, Azure Solutions Architect Expert)
• Experience with data mesh or domain-driven data architecture
• Background in a regulated industry (finance, healthcare, etc.)