Data Engineer

Fractal Analytics; New York (NY); Remote; USD 115,000 - 125,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Parental Leave (12 weeks)

Paid holidays

PTO policy

Job summary

Fractal Analytics is seeking an experienced Data Engineer to drive a large-scale AI, data, and analytics transformation for a major financial services organization. You will lead platform modernization, AI gateway migration, BI transformation, and cloud-native data engineering, enabling an enterprise AI ecosystem built on Claude LLM, OpenAI Custom GPTs, AWS, Tableau, and Alteryx.

The role involves strategy definition and migration execution across data, analytics, and AI platforms, emphasizing

Qualifications

• Bachelor's or Master's degree in CS, Data Engineering, Information Systems, Engineering, or related.
• 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 experience 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.

Responsibilities

• 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.
• 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, 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.
• 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.
• 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.
• 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.
• 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.
• Develop and optimize cloud-native solutions leveraging AWS 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.
• 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.

Skills

Python

SQL

REST APIs

Microservices

Tableau

Alteryx

Claude integration

Education

Bachelor's or Master's degree

Tools

AWS

S3

Glue

Lambda

Redshift

Bedrock

API Gateway

IAM

OpenAI

Claude

Tableau

Alteryx

Job description

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner.

Location: Remote (supporting EST hours)

Role Summary

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 LLMOpenAI Custom GPTsAWS 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 testingAccuracy testingHallucination detectionPrompt evaluationGroundedness verificationSafety and toxicity testingBias and fairness assessmentRegression testingAgent workflow validationPerformance 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.

Required 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:

• As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plans in accordance with the plan documents, which may be amended from time to time.
• You will be eligible for benefits on the first day of Employment with the Company.
• In addition, you are eligible to participate in the Company 401(k) Plan after 30 days of employment, in accordance with the applicable plan terms.
• The Company provides 11 paid holidays and 12 weeks of Parental Leave.
• We also follow a “free time” PTO policy, allowing you the flexibility to take the time needed for either sick time or vacation.

Fractal provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!