Brillio

Data Engineer

• Design and build scalable data pipelines using Spark / PySpark on Databricks
• Develop and optimize ETL/ELT workflows for large-scale data processing
• Work with AWS EMR, S3, and Hadoop ecosystem for distributed data processing
• Build and maintain data lake and data warehouse solutions
• Develop and integrate APIs for data ingestion and consumption
• Implement data processing workflows using Airflow / Autosys
• Optimize data performance using partitioning, caching, and query tuning
• Handle structured and semi-structured data from multiple sources
• Ensure data quality, governance, and reliability of pipelines
• Collaborate with cross-functional teams (Analytics, Product, Engineering)

Lead Data Engineer – AWS

• Design, develop, and maintain ETL/ELT pipelines using IICS
• Build scalable data models and transformations in Snowflake
• Implement data ingestion from structured and semi-structured sources (S3, APIs, flat files, etc.)
• Optimize Snowflake performance (clustering, micro-partitions, query tuning)
• Work with HLS datasets (claims, patient data, CRM, commercial sales, specialty pharmacy, etc.)
• Ensure data quality, governance, and compliance (HIPAA/GxP awareness preferred)
• Collaborate with business stakeholders for requirement gathering and solution design
• Support production deployments, troubleshooting, and performance tuning
• Implement CI/CD and version control best practices

Senior Data Engineer

Security Engineer

• Lead ITGC compliance efforts within the Enterprise Applications team.
• Map enterprise app processes to relevant ITGC controls (e.g., access management, change management, data backups, etc.).
• Partner with internal audit and external auditors during controls testing.
• Provide technical oversight on app-level access controls, segregation of duties, and change tracking.
• Collaborate with DevOps, security, and business teams to ensure security and compliance are embedded into application lifecycle processes.
• Guide and enable team to map and comply teams to ITGC controls and standard certification formats.

Senior Specialist, Security

Data Scientist

• Design and implement robust statistical models and machine learning algorithms for large-scale data analysis and predictive analytics
• Lead end-to-end development of data science projects, including hypothesis testing, regression analysis, classification, and forecasting
• Collaborate with cross-functional teams to define business requirements, translate them into analytical solutions, and drive measurable impact
• Optimize and automate data pipelines using Python, PySpark, and R, ensuring efficient data processing and feature engineering
• Develop, validate, and maintain probabilistic graph models and advanced statistical computing frameworks
• Utilize industry-leading ML frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn to build, train, and deploy models
• Establish rigorous model evaluation and monitoring processes using tools like Great Expectations and Evidently AI
• Mentor and guide junior data scientists, fostering technical excellence and continuous learning within the team

Principal Data Scientist

Engineer

• Engage directly with business stakeholders, VPs, clinical leads, operations owners to surface ambiguous, high-value problems and translate them into buildable AI opportunities
• Ask sharp questions, challenge assumptions, and define what a minimum viable AI solution looks like before writing a line of code
• Map existing processes end-to-end, identify where AI can eliminate friction, reduce cost, or accelerate decisions and communicate your findings in business terms
• Build lightweight scoping documents and ROI estimates that align stakeholders and set clear success criteria before development begins
• Design and build working AI prototypes within days using Claude and the modern AI development stack
• Develop full-stack AI applications spanning LLM orchestration, retrieval-augmented generation (RAG), agentic workflows, REST API integrations, and lightweight front-end interfaces
• Own your technical architecture end-to-end from prompt design to data pipeline to user interface and be able to explain every design decision to both engineering and business audiences
• Iterate based on real user feedback in the field ship early, learn fast, and drive toward production-grade quality with intention and speed
• Partner with Brillio's AI Governance team to validate, harden, and evolve prototypes into production-grade, enterprise-ready systems.
• Apply responsible AI principles bias review, explainability, HIPAA compliance, audit logging, and model monitoring as a standard part of every build.
• Document solutions clearly and completely so they can be handed off, scaled, and maintained by broader engineering teams without rework.
• Contribute to Brillio's reusable AI accelerator library turning client-specific solutions into patterns that can be deployed across engagements.
• Participate in all client business rhythm meetings sprint reviews, program steering committees, and executive status updates
• Demonstrate progress through live demos and working software not slide decks alone
• Communicate technical concepts clearly to non-technical business leaders and build the trust required to move from pilot to scale
• Surface blockers, dependencies, and risks early with clear, solutions-oriented framing
• Develop genuine expertise in your client's business, their workflows, their data, their competitive pressures, and their regulatory environment
• Understand healthcare operations deeply enough to generate your own problem hypotheses not just respond to inbound requests
• Build relationships with business counterparts that go beyond project delivery, becoming a trusted advisor on what AI can and cannot do in their environment
• Contribute to internal knowledge sharing bring learnings from client engagements back to Brillio's broader applied AI community

Forward Deployed Engineer

• Lead the design and implementation of complex data science solutions to drive business impact and inform strategic decision-making
• Develop, validate, and optimize advanced statistical and machine learning models, including regression, classification, and forecasting algorithms
• Collaborate with cross-functional teams to translate business objectives into actionable analytics projects and deliver measurable outcomes
• Mentor and guide junior data scientists, fostering a culture of technical excellence and continuous learning
• Leverage Python, R, and relevant frameworks to build scalable data pipelines and automate model deployment using tools such as KubeFlow and BentoML
• Conduct rigorous statistical analysis, including hypothesis testing, T-Test, Z-Test, and probabilistic graph modeling to uncover actionable insights
• Implement and monitor model validation, explainability, and performance tracking using tools like Great Expectation and Evidently AI
• Stay current with emerging trends in machine learning, artificial intelligence, and big data technologies to drive innovation within the team

Senior Data Science Lead

IT Support

• Define and govern enterprise architecture frameworks, standards, and reference architectures
• Develop technology roadmaps aligned to business transformation objectives
• Drive architecture governance, design reviews, and compliance adherence across programs
• Lead end-to-end cloud migration programs (AWS, Azure, GCP) from legacy/on-prem systems
• Drive application modernization initiatives, including monolith to microservices transformation and cloud-native refactoring
• Architect and enable SaaS platforms with multi-tenancy, scalability, and security
• Provide technical leadership across full-stack engineering teams

Enterprise Architect

Consultant

• Consultant role in Digital Engineering

Call Center Representative

• We are seeking a hands-on, business-savvy Contact Center Architect to own the end-to-end design of our healthcare contact center on Amazon Connect, spanning member, provider, and self-service experiences.
• The ideal candidate is a genuine “jack of all trades”: equally comfortable whiteboarding a contact flow with a business sponsor, debating IAM and PHI handling with security, and pairing with developers on a Lambda integration.
• Drive the conversation with the business — lead working sessions with operations, member/provider experience, product, and compliance stakeholders to surface goals, pain points, and the “why” behind every requirement.
• Bridge business and IT — translate business intent into clear technical requirements for development teams, and translate technical constraints and trade-offs back into language the business can act on.
• Earn and keep trust — act as the single, credible point of contact who both sides rely on; embrace the customer's perspective and represent it faithfully throughout delivery.
• Facilitate decisions — run design reviews, build consensus across competing priorities, and keep initiatives moving without losing either business value or technical integrity.
• Own the end-to-end architecture of the Amazon Connect contact center across member, provider, and self-service journeys.
• Design IVR / IVA and contact flows, routing strategies, queueing, and omnichannel (voice, chat, callback) experiences optimized for self-service and containment.
• Architect caller authentication and identity flows — including data-driven verification, integration with member/provider systems of record, and secure handling of PHI/PII.
• Establish monitoring, logging, and alerting (e.g., CloudWatch) and define the KPIs that matter — authentication rate, self-service / containment rate, average handle time, and deflection.

Contact Center Architect – Healthcare, Amazon Connect

Software Engineer

• Design and implement a scalable AWS architecture to migrate call recordings and analytics from Calabrio to Amazon Connect.
• Build serverless and microservices-based applications using AWS Lambda, Amazon API Gateway, and Amazon SQS.
• Develop dashboards and administrative tools using React, Angular, or Vue.js.
• Develop automated scripts to migrate historical call recordings, transcripts, and metadata.
• Build and maintain CI/CD pipelines using GitHub Actions, Atlassian Jenkins, or AWS CodePipeline.
• Implement encryption, access controls, and audit logging using AWS Key Management Service, AWS Identity and Access Management, and AWS CloudTrail.
• Partner with contact center, infrastructure, security, and business stakeholders.

AWS Kinesis Developer

Human Resources

• Partner with business and HR leaders to execute on a very contextual people strategy and a global talent management model
• Understand the business and propose changes to add value on people dimensions.
• Provide HR consulting and advisory to managers and leaders on improving leadership, team and organizational effectiveness through fair and consistent advice on HR programs, policies and other key people related decisions.
• Design and drive the engagement charter for the business.
• Proactively seek and drive data driven insights, conversations and decisions with the business leaders
• Work with business leaders and COEs (Rewards, OD, L&D, etc.) to evolve the design and operations of programs to meet current and/or future needs
• Drive a high performance culture through an effective implementation of the Performance management system.
• Own with business, people development and talent management strategies specific to the business context.
• Utilize total rewards principles including compensation & benefits to drive critical actions
• Partner with business leaders for proactive retention strategies.
• Design and drive short term to long term strategies for attrition control.
• Be the custodian of harboring and nurturing the mission, vision and values of Brillio
• In this role you will be responsible for managing the engagement at location

Lead, HR

• Design scalable and secure Databricks Lakehouse architectures
• Lead implementation of data engineering, ingestion, transformation, and analytics frameworks
• Define enterprise data governance and security standards using Unity Catalog (UC)
• Architect CI/CD, DevOps, monitoring, and automation for Databricks environments
• Optimize Spark workloads, cluster utilization, and platform cost efficiency
• Collaborate with business, security, infrastructure, and data teams on enterprise data initiatives
• Design data integration patterns across cloud, APIs, MDM, and enterprise systems
• Support migration and modernization from legacy data platforms to Databricks
• Establish best practices for performance, scalability, governance, and operational excellence

Senior Data Architect

DevOps Engineer

• Work directly with customer business and technology teams to design, build, and deploy AI-driven solutions
• Engage in product discovery, partner with customer stakeholders
• Translate business objectives into a clear delivery plan
• Build production-grade services, APIs, and workflow integrations using Python
• Design and deploy cloud-native components on AWS
• Troubleshoot issues in real environments
• Drive adoption by aligning stakeholders with solutions

Forward Deployment Engineer

Data Analyst

• Perform deep data analysis to identify trends, anomalies, variances, and forecasting improvement opportunities.
• Support senior data scientists with model inputs, backtesting, validation, and performance analysis.
• Monitor forecast accuracy, bias, and overall health of forecasting solutions.
• Analyze data quality issues and understand business drivers.
• Build analytical datasets and reports to support forecasting and supply chain planning.
• Develop dashboards and KPI reporting using Power BI or similar analytics platforms.
• Collaborate with business teams and data scientists to improve decision-making.
• Automate recurring analysis using SQL and Python.
• Ensure strong data governance and reliable data availability.

Senior Data Scientist, Data Analytics

• Lead Data Analyst needed in New York, NY and various unanticipated locations throughout the U.S. Utilize the power of solutions that can be driven through Visualization and ETL tools.
• Establish connection with different teams to evaluate the automation and service management offerings Python can bring in.
• Drive discussions with various teams to foresee opportunities to unify the operations console across businesses.
• Implementation of Customer Dashboard and Reports for real-time performance view of SLA.
• Work on SQL Server (or client specific RDBMS) developing customized codes and testing.
• Responsible for creating operational insights for telecom network related data from Fuze and integrate with other data sources to identify revenue growth/cost optimization/operational efficiency opportunities.
• Interpret data and define new KPIs for data analysis from multiple sources.
• Use data visualization and other data-gathering methods to either provide internal strategic direction or guide decisions for other teams for new tower builds, OFS analysis, Fallout analysis, compliance and usage adoption.
• Work on acquiring data from primary or secondary data sources and preserve the data integrity of these sources using SQL, Python and other analytical tools.
• Create powerful data visualizations using tools like Tableau and Looker. Focus on the overall service quality and timely execution of the project.
• Active participation and contribution to all service improvement initiatives to ensure they are aligned to our customers’ expectations.
• Successfully implement multiple Analytics/IT projects by providing the technology knowledge and vision to support the company’s business objectives and evaluate and recommend all software for business processes.
• Be accountable for all aspects of service delivery in conceptualization, planning, design, automation, transition, and delivery.
• Understand clearly operational definitions for all processes; understand how to measure all critical data points in the processes, improve any irregularities reported because of the Metrics Dashboards.
• Proactively initiate Process Improvements keeping in mind inputs from Audit Process. Manage Process & Framework.