Jobs at Fractal

Develop and maintain Java backend and React frontend applications for data-to-decision projects. Integrate algorithmic outputs through REST APIs, collaborate with data science, engineering, business, and product teams, create interactive infographics, participate in user acceptance testing, troubleshoot application and integration issues, and maintain technical documentation.

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.

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.

Provide L2/L3 support and enhancements for SAP BW/BW on HANA/BW/4HANA: troubleshoot data loads, process chains, routines, and reporting; perform BW inventory assessment, rationalization, performance tuning, transports, documentation, and support modernization/migration initiatives.

Design, implement, and manage GCP-based CI/CD pipelines and platform infrastructure. Automate provisioning with IaC (Terraform/ARM), maintain build/release pipelines, manage Git workflows, integrate automated testing, enforce security best practices, and implement monitoring, logging, and tracing. Collaborate with development and security teams to ensure reliable deployments and platform health.

The role involves leading Azure architecture engagements, designing cloud-native solutions, mentoring teams, and collaborating with various stakeholders to optimize cloud adoption and security.

Lead end-to-end AI solutions for clients, manage project delivery and people, partner with sales for business development, collaborate with engineering/MLOps/DevOps, ensure data quality, model training, tuning, deployment, monitoring, and provide executive updates on status and risks.

Lead AIML-ADM efforts to design, prototype, and deliver end-to-end AI/ML solutions. Manage and mentor data scientists, engage stakeholders, scope problems, perform EDA, build and deploy models (segmentation, churn, LTV, forecasting, recommenders, optimization), and monitor outcomes using statistical and machine learning methods.

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.

The Data Modeller will design data models, conduct reviews, collaborate with data teams, and maintain industry knowledge to enhance systems.

As an Azure Data Engineer, you will innovate and maintain data engineering services for Fortune clients, develop software for large projects, and utilize Azure components for solutions.

Senior Databricks MLOps Engineer responsible for automating the end-to-end ML lifecycle: CI/CD, packaging, deployment, scheduling, monitoring, and reproducible experiments. Build frameworks and pipelines, integrate embedding/LLM components (RAG, vector DBs, LangChain), optimize ML workloads, and collaborate with data scientists and platform teams to productionize models for Claims Payment Integrity.

Lead RGM data science projects for CPG/consumer durables: maintain and upgrade models, design solution frameworks, run AI pipelines, perform data wrangling and visualization, prototype innovations, liaise with engineering/MLOps, lead small DS teams, enforce code standards, and guide client- facing discussions and workshops.

Responsible for developing and maintaining web applications using React and Python, collaborating with teams to ensure project success.

Fractal Analytics seeks a Hacker-Mind AI Engineer for rapid prototyping of AI solutions, problem-solving, and collaboration with teams and clients, leveraging cutting-edge technologies.

The Lead Architect will evaluate technology, create best practices, and ensure smooth project deliveries while collaborating with data teams. Requires expertise in GCP and data solutions.

Design, develop, and maintain cloud data infrastructure, data pipelines, data models, and storage solutions on Azure. Ensure data quality, integrate with cross-functional teams, optimize distributed systems, and establish data engineering best practices.

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.