Job ID: 112314-1
Job Title: Technical Architect
Location: Phoenix, Arizona / 100% onsite
Duration: 6 months
Pay Rate: $55-$60/hr on W2/C2C
PLEASE NOTE: This position requires strong hands-on experience in implementing Data Platform using Java/Springboot/Kafka/Microservices skillsets.
Role Overview:
We are seeking an experienced Technical Architect to own the deep technical design and implementation of the event-driven data ingestion layer within the Enterprise Data Platform(EDP). This role is hands-on and inward-facing: the Technical Architect defines and governs how source services, Java/Spring Boot microservices, Apache Kafka, and downstream storage (ADLS Delta) fit together, ensuring reliability, scalability, and engineering rigor across the ingestion pipeline. The ideal candidate combines strong Java/Spring Boot engineering depth with practical experience designing Kafka-centric, event-driven microservice architectures, including transactional outbox patterns, CDC pipelines, and idempotent consumers.
Key Responsibilities:
• Own the end-to-end technical design of Java/Spring Boot microservices that produce, consume, and process Kafka events for the EDP ingestion layer (e.g., the Enterprise Entity Service, batch/stream ingestion microservices).
• Design and implement the transactional outbox pattern for multiple event types (e.g., sales, inventory), including single-topic-plus-DLQ strategies, aggregate-keyed ordering, and schema-governed event envelopes (event_id, aggregate_id, sequence, occurred_at, schema_version).
• Define CDC-based event capture using Debezium (or equivalent) and the Outbox Event Router pattern to publish business-data changes to Kafka with at-least-once delivery guarantees.
• •Architect idempotent, exactly-once-processing-safe consumers, covering dedupe-by-event-id, retry/backoff policies, circuit breakers, and DLQ handling for transient and poison-message failures.
• Design incremental/watermark-based extraction services in Spring Boot (e.g., Spring Batch with JdbcPagingItemReader, ShedLock for single-flight scheduling) for SQL Server and other relational sources feeding Kafka.
• Define the technical contract between Kafka and the storage layer, including Kafka Connect sink connectors (Iceberg/Delta on ADLS), schema evolution via Schema Registry, and medallion (Bronze/Silver/Gold) data layering.
• Set coding standards, review architecture and code for Java/Spring Boot services, and mentor engineers and senior developers on microservice design patterns, resiliency, and performance tuning.
• Establish retry, backoff, and range-based retry strategies across ingestion layers (storage reads, DB writes, Kafka consumes, relay publishing), and define circuit-breaker and alerting thresholds.
• Collaborate with the Lead Solution Architect and enterprise architects to translate target-state data platform architecture into detailed technical blueprints and implementation plans.
• Define monitoring and operational practices (DLQ depth, consumer lag, reject rates) using tools such Dynatrace.
• Support production troubleshooting of cluster performance, infrastructure scaling, and pipeline errors for the services under their ownership.
• Provide hands-on leadership for Enterprise Data Platform Modernization initiatives, including current-state assessments, architecture transformation, migration planning, and modernization roadmaps.
• Lead customer workshops to understand business requirements, use cases, pain points, and future-state needs.
• Define Target State and Transition State Architectures for enterprise-scale data and analytics platforms.
• Lead architecture blueprinting, solution definition, and technology evaluation.
• Translate business requirements into technical capabilities, architecture artifacts, and implementation roadmaps.
• Drive technology selection and evaluation across cloud-native, open-source, and commercial platforms.
• Develop implementation strategies, effort estimate, infra sizing & cost model
• Define data platform operating models, engineering practices, architecture standards, and governance frameworks.
• Guidance on scalability, performance, security, reliability & operational excellence
• Design modern data integration architectures, including CDC & event-streaming platforms
• Evaluate and recommend open-source technologies for enterprise adoption.
• Collaborate with business stakeholders, product teams, architects, and engineering teams throughout the engagement lifecycle.
• Support pre-sales activities, solution development, proposals, architecture reviews, and executive presentations.
• Mentor engineering and architecture teams on modern data platform technologies, architecture patterns, and best practices.
Mandatory Skills:
Core Technical Stack:
• Strong hands-on experience in Java (Java 10+) and Spring Boot, including Spring Batch, Spring Kafka, and Spring Integration.
• Deep working knowledge of Apache Kafka: producers/consumers, partitioning and keying strategies, consumer groups, offsets, Kafka Connect, and Schema Registry.
• Experience designing microservices using event-driven patterns: transactional outbox, CDC (Debezium), saga/idempotent consumer patterns, and dual-write avoidance.
• Practical experience with relational databases (SQL Server, PostgreSQL) including watermark/incremental extraction, change tracking/CDC, and transactional writes.
• Familiarity with modern lakehouse storage formats — Delta Lake and/or Apache Iceberg on Azure Data Lake Storage (ADLS) — and query engines such as Spark or Databricks.
• Experience with distributed system resiliency patterns: retry with exponential backoff, circuit breakers, dead-letter queues, and idempotency guarantees.
Architecture & Leadership:
• Proven experience as a Technical Architect or Senior Engineer leading the technical design of data ingestion or event-streaming platforms.
• Ability to produce detailed design documentation, architecture diagrams, and implementation guides for stakeholder review.
• Strong understanding of scalability, performance tuning, security, and operational monitoring for high-throughput streaming systems.
• Experience mentoring engineering teams and enforcing coding/design standards across a microservices codebase.
Technical Expertise:
• Java | Spring Boot | Microservices | Kafka | Cassandra | SQL | Debezium
• Cloud Storage Azure
• Nice to have Python | Spark | Informatica
Data & Analytics
• Real-Time Data Processing
• Event-Driven Architecture
• CDC Architecture
• API and Service Integration
• Enterprise Architecture Patterns
Preferred Industry Experience:
• Retail
• Grocery Retail
• Consumer Goods
• E-Commerce
• Omnichannel Commerce
• Supply Chain
• Merchandising & Inventory Analytics
Educational Qualifications:
• Bachelor's or Master's Degree in Computer Science, Engineering, Information Technology, or a related discipline.
Desired Candidate Profile:
• 10+ years of experience in Software engineering and architecture.
• Proven experience architecting and delivering enterprise-scale cloud data platforms.
• Strong consulting mindset with the ability to engage CXO and senior business stakeholders.
• Ability to independently drive architecture workstreams from discovery through roadmap definition.
• Experience leading geographically distributed teams and large transformation programs.
• Strong problem-solving and communication skills with a focus on business outcomes.
Experience Required: 10 & Above