Jobs at Fractal

The Senior Data Modeler is responsible for designing and managing data models, ensuring data accuracy, compliance, and alignment with business needs.

Lead product and visual design for an optimization program: design internal tools and dashboards, create A/B test variations for email and digital channels, and produce high-quality communications (decks, newsletters, launch assets). Own end-to-end design from discovery through prototypes and developer handoff, maintain design system, and collaborate closely with data scientists, engineers, producers, and program stakeholders.

Build production-grade LLM applications (agentic chatbots, semantic search, RAG systems), fine-tune foundation models, implement RAG and agent architectures, integrate AI assistants with systems, design evaluation/governance pipelines, collaborate with cross-functional teams, and mentor junior data scientists.

Lead supply chain analytics engagements: manage client teams, design data-driven solutions for demand forecasting, inventory and network optimization, drive key initiatives to closure, and provide thought leadership in supply chain analytics.

The Engagement Manager will lead analytics and AI-driven programs, manage client relationships, build high-performing teams, and innovate solutions using decision science and data science.

The Account Growth Manager will manage client relationships, drive strategic growth, and ensure successful sales and margin targets by leveraging AI and data-driven solutions.

Design, build, and optimize scalable Azure Databricks data pipelines and data lake/warehouse solutions. Develop ETL/ELT workflows using PySpark and Spark SQL, implement data ingestion, quality, monitoring, and CI/CD automation, and provide technical leadership while ensuring security, governance, and performance tuning for analytics and AI initiatives.

Design, build, and optimize scalable Azure Databricks data pipelines and data lakes. Develop ETL/ELT workflows using PySpark and Spark SQL, implement data quality and monitoring, optimize Spark jobs, support data warehouse initiatives, automate CI/CD deployments, and ensure security and governance while collaborating with stakeholders and mentoring junior engineers.

Design and govern scalable Azure data platforms; build ETL/ELT batch and streaming pipelines; implement lakehouse/warehouse and data quality frameworks; enable metadata, lineage, observability, CI/CD and IaC; lead migrations, mentor engineers, and work with stakeholders across BI, AI/ML, governance, and infrastructure.

Design, build, and optimize enterprise-scale data platforms and ETL/ELT pipelines on Azure Databricks. Implement Medallion/Lakehouse architectures, integrate streaming and batch sources, tune Spark jobs and clusters, create CI/CD for deployments, enforce governance/security, troubleshoot production issues, and mentor junior engineers.

Design and lead implementation of enterprise-scale Azure and Databricks data platforms, including lakehouse, data mesh, streaming and batch pipelines. Drive security, governance, performance, cost optimization, mentor teams, and support client engagements and proposals.

Lead go-to-market and revenue for the Cogentiq Invoice-to-Cash product: drive new business, manage full sales lifecycle, design commercial models, collaborate cross-functionally, and secure enterprise deals while supporting onboarding and growth.

Design, build, and maintain scalable data pipelines on GCP; migrate data from Teradata to BigQuery; write optimized SQL and Python ETL/ELT; implement monitoring, testing, validation, and reconciliation; document processes and collaborate with analysts, architects, and stakeholders.

Lead delivery and growth for Fortune 50 hi-tech accounts, driving multi‑million AI and GenAI programs. Manage global cross‑functional teams, executive relationships, account economics, proposals, and expand long‑term partnerships while ensuring delivery quality and client satisfaction.

The Cloud Platform Engineer will design and implement cloud infrastructure, automate deployments using Terraform and Argo, develop serverless applications, and collaborate with teams to maintain robust cloud services.

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