Mid-Level Data Architect

Harnham; Town of Texas (WI); On-site; USD 140,000 - 190,000; Full time

Job summary

Harnham is seeking a Data Architect to join our fraud data organization to shape the future-state data architecture and guide migrations across a multi-business-line environment.

You will collaborate with engineering and business stakeholders to build scalable cloud-native solutions supporting batch, streaming, and AI-driven workloads, while driving data governance and standardization across teams.

Qualifications

• Hands-on experience with Snowflake.
• Experience designing batch, streaming, and real-time data platforms.
• Experience defining enterprise data standards, reference architectures, and migration roadmaps.
• Ability to translate business outcomes into scalable technical architecture.
• Strong communication and executive stakeholder management skills.
• Experience working within large, complex enterprise organizations.

Responsibilities

• Assess current-state data architecture and integration patterns.
• Define target-state architecture, migration strategies, and roadmaps.
• Design reference architectures for batch, near real-time, and real-time processing.
• Architect scalable, low-latency data pipelines for fraud and risk use cases.
• Lead event-driven data solutions using Apache Kafka.
• Partner with product, engineering, and business teams to translate objectives into architecture.
• Evaluate options balancing cost, risk, and value.
• Establish reusable patterns and standards across teams.
• Promote automation, CI/CD, and operational excellence.
• Drive data governance and data quality across the lifecycle.
• Support adoption of AI-enabled architecture patterns like RAG and vector databases.

Skills

Snowflake

Architecture

Batch/Streaming/Real-time

Data governance

Executive communication

Large enterprises

AI-enabled patterns

Event-driven architectures

Tools

Apache Kafka

DBT

Fivetran

Job description

Work Authorization: Must be authorized to work in the U.S. without sponsorship (now or in the future)

About the Company

This large, established enterprise is seeking a Data Architect to join a growing data organization focused on fraud detection and prevention. This role offers the opportunity to influence the future-state data architecture of a complex, multi-business-line organization while helping modernize cloud and AI capabilities.

The ideal candidate will combine strong architectural thinking with hands-on technical expertise, particularly around real-time data processing and event-driven architectures. This is not a "diagram-only" architecture role. The team is looking for someone who can provide technical recommendations, validate solutions, and partner closely with engineering and business stakeholders to drive outcomes.

About the Role

This is not a traditional architecture role focused on creating diagrams and handing work off to engineering teams.

As a Data Architect, you'll help define and build the organization's future-state data architecture while working closely with engineering teams to validate technical decisions and guide implementation. You'll assess the current environment, design migration strategies, establish reusable architectural patterns, and help build scalable cloud-native solutions supporting batch, streaming, and AI-driven workloads.

Whether joining the Fraud team focused on real-time data or the Enterprise Architecture team defining organization-wide standards, you'll have significant influence over technical direction and long-term platform strategy.

Key Responsibilities

• Assess, document, and improve current-state data architecture and integration patterns.
• Define target-state architecture, migration strategies, and implementation roadmaps.
• Design and maintain reference architectures for batch, near real-time, and real-time data processing.
• Architect scalable, low-latency data pipelines supporting fraud and risk-related use cases.
• Lead the design of event-driven data solutions using Apache Kafka.
• Partner with product, engineering, and business teams to translate business objectives into technical architecture.
• Evaluate strategic options by balancing cost, risk, timeline, and business value.
• Establish reusable frameworks, templates, and architectural standards that can be leveraged across multiple teams.
• Promote automation, CI/CD practices, and operational excellence across the data ecosystem.
• Drive data governance, data quality, and best practices throughout the data lifecycle.
• Contribute to the adoption of modern AI-enabled architecture patterns, including retrieval-augmented generation (RAG), vector databases, and agent-based systems.

Must Haves

• Hands-on experience with Snowflake
• Experience designing batch, streaming, and real-time data platforms
• Experience defining enterprise data standards, reference architectures, and migration roadmaps
• Ability to translate business outcomes into scalable technical architecture
• Strong communication and executive stakeholder management skills
• Experience working within large, complex enterprise organizations

Nice to Have

• Background in financial services, healthcare, travel, or other highly regulated/complex industries.
• Prior experience as a Data Engineer or Software Engineer before moving into architecture.
• Exposure to DBT, Fivetran, or similar modern data tooling.
• Familiarity with AI-enabled data architectures, including: RAG, Vector databases, MCP, and Agentic AI concepts.
• Experience defining reusable architecture patterns and enterprise standards.

Why Join

• High-visibility role with direct impact on data strategy and modernization initiatives.
• Opportunity to help design the future-state architecture rather than inherit a mature environment.
• Significant exposure to real-time fraud data challenges at enterprise scale.
• Opportunity to work with emerging AI architecture concepts and modern cloud technologies.
• Collaborative team culture focused on knowledge sharing, mentorship, and end-to-end ownership.
• Exposure to multiple business functions and complex enterprise data ecosystems.