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Fractal Analytics Inc. is seeking an experienced Data Engineer to support a large-scale AI, data, and analytics transformation initiative within a leading Financial Services organization.
You will drive platform modernization and AI gateway migration, shaping the cloud-native data engineering strategy and delivering migration roadmaps across enterprise data, analytics, and AI platforms. The role requires hands-on experience with AWS, Python, SQL, REST APIs, Tableau, and Alteryx, and a track
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.
Remote (supporting EST hours)
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.
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.
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.
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.
At Fractal, towards our goal of “powering every human decision in the enterprise”, our partnerships and alliances help in creating and delivering a compelling suite of solutions to unlock value. We partner with companies from around the globe, leaders in their respective fields. With Fractal’s expertise in artificial intelligence, design, engineering, and digital transformation, combined with the data, technology, and software platforms from our partners, we create cutting‑edge solutions to problems in the business world. We understand how critical and timely decision triggers, and information, empower our clients to create, unlock, deliver, and realize value. Together with our partners, our goal is to serve each client in their end‑to‑end data‑to‑decision journey.