Operating within a multi-cloud environment, the Technical Lead will orchestrate a dual-track strategy: maintaining the reliability of legacy systems while designing a vendor-agnostic, high-performance architecture that leverages the strengths of AWS, Microsoft Fabric, and Google Cloud solutions. The role is central to eliminating technical debt, standardizing engineering practices, and enabling seamless data accessibility across platforms.

Beyond architecture, this position provides strong technical mentorship, guiding Data Engineers and RPA Developers to adopt modern data paradigms, engineering excellence standards, and governance frameworks that ensure long-term platform sustainability.

• Architect and implement a Medallion data pipeline framework (Bronze, Silver, Gold) that ensures structured progression from raw ingestion to decision-ready, high-integrity datasets.

• Define and execute a multi-cloud orchestration strategy that integrates AWS, Microsoft Fabric, and Google Cloud services into a cohesive, interoperable data mesh.

• Evaluate and modernize existing AWS-hosted components and legacy batch-update systems, transitioning toward a unified, version-controlled, cloud-native infrastructure.

• Design and oversee ingestion strategies for more than 400 diverse data sources, including APIs, affiliate platform integrations, and RPA-driven collection processes.

• Establish robust data governance mechanisms, including data contracts, schema validation at ingestion points, and automated observability frameworks.

• Define and enforce strict software development standards, eliminating manual and ad-hoc processes in favor of scalable, automated workflows.

• Standardize the transformation layer using modular ELT frameworks to automate complex operational logic (e.g., commission calculations and business rules).

• Implement CI/CD best practices and observability mechanisms to ensure pipeline reliability, automated alerting, and proactive issue resolution.

• Balance architectural foresight with pragmatic execution, ensuring business continuity during system modernization efforts.

• Collaborate closely with DevOps, Infrastructure, Product, and BI teams to ensure alignment between platform capabilities and business objectives.

• 5+ years of experience in Data Engineering, Software Architecture, or related fields.

• Minimum 2 years in a senior or leadership capacity guiding architectural decisions and mentoring engineering teams.

• Proven experience leading modernization initiatives within complex data environments.

• Demonstrated experience designing scalable data architectures in production environments.

• Strong command of Python and advanced SQL, with the ability to design optimized and scalable transformations.

• Deep practical expertise in at least one primary cloud ecosystem (AWS or GCP).

• Significant exposure to Microsoft Fabric or comparable lakehouse/data warehouse environments.

• Proven experience in cross-cloud data integration and orchestration.

• Experience designing and implementing modular ELT pipelines using modern transformation frameworks.

• Strong understanding of scalable ingestion strategies, including APIs, event-based systems, and RPA-driven pipelines.

• Proficiency in version control systems (Git) and modern CI/CD deployment practices.

• Familiarity with Infrastructure as Code (e.g., Terraform) is highly advantageous.

• Knowledge of data governance practices, schema validation techniques, and observability tooling.

• Understanding of RPA frameworks and their integration into broader data engineering workflows is highly desirable.