2 SYSTEM ARCHITECT (DATA + MULESOFT + AWS ) OVERVIEW OF ROLE • Design and deliver scalable, enterprise-grade data solutions across AWS and Databricks, covering end-toend architecture, ingestion, data modeling, transformation, orchestration, APIs, and downstream integrations. • Lead the development and modernization of high-volume, business-critical data products and platforms, translating complex business and technical requirements into secure, scalable, and maintainable solutions. • Establish architectural standards, coding practices, reusable frameworks, and engineering best practices to drive consistency, quality, and maintainability. • Define robust orchestration, monitoring, and operational patterns to ensure performance, scalability, reliability, resilience, and cost optimization. • Provide hands-on technical leadership across solution design, architecture reviews, code reviews, development, debugging, and complex technical decision-making. • Lead cross-functional delivery across Product, Business, Architecture, Data, API, QA, and Platform teams within Agile environments. • Drive data quality, governance, observability, security, and production readiness across data products and platforms. • Mentor engineers and technical leads while promoting engineering excellence and continuous improvement. REQUIRED QUALIFICATIONS • 10+ years of experience in Data Engineering / Data Architecture, including data modeling, database design, ETL/ELT, data ingestion, legacy system migration, and processing large-scale datasets. • 3+ years of hands-on experience with Databricks, Apache Spark, and PySpark, including Spark performance optimization. • Strong hands-on experience with AWS services including S3, Lambda, Aurora/RDS, Step Functions, and CloudWatch. • Strong SQL and Python development skills with proven experience in developing, debugging, and optimizing data solutions. • Experience designing and implementing robust data orchestration workflows, including scheduling, dependencies, retries, error handling, monitoring, and operational resilience. • Strong understanding of software engineering practices, including coding standards, code reviews, testing, reusable frameworks, and development best practices. • Experience with REST APIs and API integrations, including request/response flows, integration patterns, and downstream data integrations. • Working knowledge of MuleSoft or similar API and integration platforms. • Experience with CI/CD practices and tools such as Azure DevOps or equivalent platforms. • Strong understanding of data quality, validation, reconciliation, monitoring, and production support practices. • Experience creating, reviewing, and maintaining functional and technical documentation. • Strong understanding of Agile methodologies, including sprint planning, backlog refinement, and iterative delivery. 3 • Proven experience working with and leading cross-functional teams comprising Data Engineering, API, QA, Architecture, Product, and Business stakeholders. • Proven experience leading, mentoring, and providing technical guidance to data engineers and technical leads. • Excellent verbal and written communication skills, with the ability to effectively communicate complex technical concepts to both technical and business stakeholders. PREFERRED QUALIFICATIONS • Understanding of AWS or similar cloud infrastructure optimization and cost management, including evaluating compute, storage, and processing options. • Data engineer with API development experience • Experience with Redis or any in-memory database • Relevant AWS Certifications in cloud computing, data engineering, and/or solutions architecture. • 8 + years of experience writing and maintaining infrastructure code. • 8 + years of experience using any automation tools and ADO CI/CD pipelines