Jobs at Fractal

Lead and run enterprise data governance: develop frameworks, policies, metadata and lineage, lead data quality remediation, define stewardship and ownership, ensure regulatory compliance (GDPR/CCPA), set KPIs, train staff, and manage a governance team.

The Data Steward ensures data governance and quality by developing solutions, creating data metrics, conducting profiling, and collaborating with stakeholders to maintain data integrity.

Design and scale enterprise Agentic and Generative AI platforms, focusing on microservices, orchestration, reliability, and cloud architecture. Lead teams to develop production-ready AI systems.

Drive business growth by selling consulting and technical services, managing client relationships, and collaborating with Microsoft for joint sales opportunities.

This role involves planning and designing Azure infrastructure, developing cloud solutions, mentoring teams, and ensuring cloud security and compliance.

The Engagement Manager will lead analytics-driven programs, manage client relationships, and innovate solutions in decision science and AI. Responsibilities include fostering collaboration, mentoring teams, and contributing to practice growth.

The AWS Data Engineer will work on designing and building cloud-based solutions, utilizing AWS services, and integrating systems for clients. Requires experience with various AWS tools and Java development.

The Senior Fullstack Engineer will design, develop, and maintain enterprise web applications while collaborating with data teams and managing junior engineers.

The Sr. Data Scientist will lead the implementation of AI solutions, focusing on multi-agent GenAI workflows, LLM orchestration, and scalable applications while ensuring quality and governance in delivery.

Gather and analyze client requirements, identify gaps, and develop BI dashboards using Qlik Sense/QlikView, Power BI, or Tableau. Present dashboards and storylines to end users, collaborate with distributed teams, and manage multiple projects under pressure.

Owner of full-stack feature implementation across web, API, cloud, DevOps, and AI-enabled capabilities. Design, build, test, deploy, monitor, and optimize scalable, secure production systems; integrate LLMs and RAG; enforce code quality, mentor juniors, and collaborate with architects, TPMs, product, QA and platform teams.

Advise clients on developing and implementing data governance strategies. Design policies, frameworks, and practices for data quality, privacy, metadata management, and security. Deliver governance projects, build capability with frameworks and accelerators, and promote governance awareness across stakeholders and committees.

Develop and maintain an AWS Lex based chatbot workflow and integration with backend systems using API, along with Jenkins for DevOps.

The Sales Hunter will drive new business in TMT accounts, manage client relationships, educate clients on Fractal's solutions, and lead sales initiatives using advanced analytics expertise.

The Senior Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality, integrity, and alignment with business objectives. Responsibilities include collaborating with teams and establishing best practices for data engineering.

Lead and grow a portfolio of payer accounts (insurers, TPAs, government programs); act as trusted advisor, manage contracts and SLAs, collaborate with analytics/product teams, monitor KPIs/compliance, and identify upsell/cross-sell opportunities.

The Enterprise Architect will define and lead strategies for cloud, data, analytics, and AI platforms, focusing on scalable and secure systems using Microsoft Azure and Databricks, while ensuring compliance and governance across the organization.

Lead the Business Intelligence center of excellence by managing teams, building BI practices, and optimizing BI solutions using various tools.

The Sales Leader will oversee sales for corporate L&D, develop strategies, lead a sales team, manage client relationships, and achieve revenue goals.

Design and maintain scalable data pipelines in enterprise-scale data warehousing projects using GCP and Python frameworks.