SYSTEM ARCHITECT (DATA + MULESOFT + AWS )

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