Jobs at Fractal

Consolidate procurement and ERP data to produce dashboards and reports (Power BI, Tableau). Provide procurement analytics, identify cost-saving opportunities, optimize workflows, implement automation, and partner with procurement leaders to define and track KPIs and communicate insights to stakeholders.

Lead AWS data architect responsible for designing, building and operationalizing large-scale enterprise data platforms and pipelines on AWS. Re-architects on-premises stores to cloud, mentors engineers, runs client workshops, and delivers proofs-of-concept using Spark, Databricks, Glue, Redshift, Snowflake and related AWS services.

Lead a team of data scientists in developing and deploying machine learning models, ensuring code quality, documentation, and smooth industrialization of projects.

Design and implement data solutions on Azure, optimize data processing frameworks, enforce governance policies, and enable BI reporting while collaborating with teams.

As a Data Engineer, you will innovate and maintain technology services, develop software systems for large projects, and work across all SDLC phases.

Design, implement, and manage multi-cloud CI/CD pipelines and automation. Use IaC (ARM templates/Terraform) to provision Azure resources, maintain build agents and release pipelines, manage Git repos in Azure DevOps, integrate automated testing, implement monitoring, logging, and security best practices, and collaborate with teams to resolve vulnerabilities.

Lead development, calibration, and operationalization of Market Mix Models (MMM). Build data pipelines, integrate experiments, quantify channel ROI and elasticity, recommend budget allocation via optimization engines, and communicate insights to marketing and senior stakeholders while ensuring reproducibility and continuous model improvement.

Lead NLP and generative AI solutions end-to-end: build intent/entity extraction, classification, summarization, search, and chatbot systems. Design, fine-tune, and evaluate LLMs and traditional NLP models, implement production-ready pipelines, collaborate cross-functionally, and drive client-facing consulting engagements in financial services.

Design, build, and maintain scalable AWS data pipelines and CI/CD for data workflows. Extract and integrate data from SAP HANA, BW, and ABAP. Implement automated deployments, monitor pipelines, resolve incidents, perform root cause analysis, and enforce data governance, security, and performance optimization.

The role involves designing and building data systems using various technologies, especially within Microsoft Azure, and requires experience in system integration and data warehousing.

The Senior Data Scientist will lead AI/ML projects, manage a data science team, implement analytical solutions, and leverage data for business insights.

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

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.

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.

The Senior Consultant will lead analytics consulting efforts, manage client relationships, develop analytics solutions, mentor a team, and drive project execution across APAC.

Lead design and delivery of enterprise Digital Operations (DigiOps) and data platform solutions using Azure and Databricks. Drive cloud migration, scalable ETL/ELT pipelines, data quality and governance, DevOps/CI-CD, automation, and stakeholder engagement while mentoring cross-functional teams to ensure operational excellence and data-driven decision making.

Work with enterprise customers to design, build, and deploy production-grade AI solutions on the Cogentiq platform. Implement integrations with enterprise systems, develop connectors, backend services, and microservices, ensure scalability, security and observability, troubleshoot deployments, and turn deployment learnings into reusable platform capabilities.

Design, build, and maintain Azure-based data infrastructure and pipelines. Implement data models and schemas, ensure data quality, optimize distributed storage and processing (Databricks/PySpark), and establish engineering best practices while partnering with cross-functional teams.

Design, develop, and maintain interactive Tableau dashboards and reports. Translate business needs into technical specifications, optimize SQL ETL queries, ensure data accuracy and performance, and collaborate with stakeholders to deliver actionable insights.

Design, implement, and manage AWS-based CI/CD pipelines and automation. Provision infrastructure via IaC (Terraform/ARM), manage Git workflows, build agents, and release pipelines. Integrate automated testing, implement monitoring, logging and tracing, and collaborate on security assessments for cloud resources. Maintain Docker/Kubernetes platform components and optimize deployment processes.