Jobs at Fractal

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.

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

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.

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 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.

Consult with CPG/FMCG clients on Revenue Growth Management analytics programs, focusing on pricing strategies, promotion analysis, and optimizing revenue growth while leading engagements across diverse global markets.

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

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

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