[Hiring] Data Engineer @Fractal Analytics

Role Description

We are seeking an experienced Data Engineer to support a large-scale AI, Data, and Analytics transformation initiative within a leading Financial Services organization. This role will be responsible for driving platform modernization, AI Gateway migration, BI transformation, AI evaluation framework development, and cloud-native data engineering.

The successful candidate will play a key role in supporting the organization's AI ecosystem built on Claude LLM, OpenAI Custom GPTs, AWS, Tableau, and Alteryx, while helping define strategy and execute the migration of enterprise AI and analytics platforms.

Key Responsibilities

• Platform Migration & Modernization
  • Design and execute migration strategies for enterprise data, analytics, and AI platforms to AWS cloud environments.
  • Assess legacy architectures and define target-state data and AI platform architectures.
  • Lead migration planning, implementation, testing, and production deployment activities.
  • Optimize platform performance, scalability, resiliency, and operational efficiency.
  • Develop migration roadmaps and implementation plans aligned with business and technology objectives.
• AI Gateway Engineering & Migration
  • Design, develop, and support enterprise AI Gateway solutions enabling governed access to AI services.
  • Lead the migration of AI Gateway capabilities from Portkey to Apigee, including architecture design, implementation planning, and execution.
  • Develop and maintain integration frameworks connecting enterprise applications to Claude LLM, OpenAI Custom GPTs, AWS Bedrock, and AI services.
  • Implement authentication, authorization, observability, rate limiting, usage tracking, and audit capabilities.
  • Create reusable APIs and services that enable secure and scalable AI adoption across the organization.
  • Establish operational monitoring and governance controls for AI platform usage.
• AI Evaluation Framework & Tool Development
  • Define enterprise AI evaluation, testing, and validation frameworks for GenAI applications, AI agents, and LLM-powered solutions.
  • Build evaluation tooling and automation capabilities covering:
    • Functional testing
    • Accuracy testing
    • Hallucination detection
    • Prompt evaluation
    • Groundedness verification
    • Safety and toxicity testing
    • Bias and fairness assessment
    • Regression testing
    • Agent workflow validation
    • Performance benchmarking
  • Develop evaluation datasets, benchmark suites, scoring methodologies, and approval criteria.
  • Implement automated testing pipelines integrated into AI development and deployment workflows.
  • Create evaluation dashboards and reporting capabilities for engineering, governance, and business stakeholders.
• AI Monitoring & Observability
  • Design and implement monitoring frameworks for AI applications, agents, and AI Gateway services.
  • Develop solutions to monitor:
    • Model performance
    • Service latency
    • Token consumption
    • User adoption
    • AI quality metrics
    • Cost and utilization trends
    • Production incidents and failures
  • Implement alerting, troubleshooting, and operational support processes.
  • Build observability dashboards supporting engineering, operations, and governance teams.
• BI Transformation Strategy & Implementation
  • Define strategy and implementation roadmap for enterprise BI modernization initiatives.
  • Support Alteryx retirement and migration of analytics workflows to strategic cloud-based platforms.
  • Lead migration strategy and execution for Tableau Cloud adoption.
  • Assess existing reporting, dashboards, workflows, and dependencies to establish migration priorities.
  • Design scalable and governed analytics architectures supporting self-service business intelligence.
  • Collaborate with business and analytics teams to modernize reporting ecosystems and improve user adoption.
• Data Engineering & Integration
  • Build and maintain scalable ETL/ELT data pipelines supporting AI, analytics, and reporting workloads.
  • Design ingestion, transformation, and orchestration frameworks for structured and unstructured datasets.
  • Enable creation of high-quality data products for AI model development, evaluation, and business intelligence.
  • Implement data quality, metadata management, lineage, and governance capabilities.
  • Support integration between enterprise applications, AI platforms, and analytics tools.
• AWS Data Platform Development
  • Develop and optimize cloud-native solutions leveraging AWS technologies including: S3, Glue, Lambda, Redshift, Bedrock, API Gateway, IAM.
  • Implement CI/CD, infrastructure automation, and deployment best practices.
  • Support platform engineering efforts ensuring secure, scalable, and compliant deployments.
• Security, Governance & Compliance
  • Implement data governance, security, privacy, and compliance requirements across AI and analytics platforms.
  • Ensure adherence to Financial Services regulatory standards and enterprise risk controls.
  • Support audit readiness through monitoring, documentation, and operational transparency.
  • Enable secure handling of customer, financial, and sensitive business data.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related discipline.
• 5+ years of experience in Data Engineering, Platform Engineering, Cloud Engineering, or Analytics Engineering.
• Strong experience delivering cloud migration and platform modernization initiatives.
• Hands-on expertise with:
  • AWS (S3, Glue, Lambda, Redshift, Bedrock, API Gateway, IAM)
  • Python
  • SQL
  • REST APIs and microservices
  • Tableau
  • Alteryx
• Experience integrating applications with Claude, OpenAI, or similar LLM platforms.
• Experience designing and implementing AI testing, evaluation, and monitoring solutions.
• Strong understanding of data architecture, ETL/ELT development, and cloud-native engineering.
• Experience supporting enterprise-scale platform migration programs.
• Knowledge of data governance, security, and compliance requirements.
• Excellent analytical, problem-solving, and stakeholder management skills.

Preferred Qualifications

• Experience building or managing enterprise AI Gateway platforms.
• Experience leading migration initiatives from Portkey, Kong, MuleSoft, Apigee, or similar API/AI Gateway solutions.
• Experience defining AI evaluation frameworks for:
  • LLM applications
  • RAG systems
  • AI copilots
  • Agentic AI solutions
• Familiarity with:
  • Vector databases
  • Prompt engineering
  • Retrieval-Augmented Generation (RAG)
  • AI observability platforms
  • Agent orchestration frameworks
• Experience supporting Alteryx-to-cloud modernization programs.
• Experience implementing Tableau Cloud migrations and BI transformation initiatives.
• Financial Services domain experience across Banking, Capital Markets, Asset Management, Wealth Management, or Insurance.
• AWS Data Engineer, Solutions Architect, or Machine Learning certifications.
• Exposure to AI governance and model risk management frameworks.

Pay

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $115,000 - $125,000. In addition, you may be eligible for a discretionary bonus for the current performance period.

Benefits

• Health, dental, vision, life insurance, and disability plans in accordance with the plan documents.
• Eligible for benefits on the first day of Employment with the Company.
• Participation in the Company 401(k) Plan after 30 days of employment.
• 11 paid holidays and 12 weeks of Parental Leave.
• “Free time” PTO policy, allowing flexibility for sick time or vacation.