Jobs at phData

Design and implement end-to-end cloud data and AI solutions, lead and mentor engineers, ensure performance, security, and scalability. Develop production-ready systems using Java/Python/Scala and SQL; work across Snowflake, major cloud platforms, and data integration tools. Create technical presentations, PoCs, architecture diagrams, and detailed solution documentation while interfacing with clients.

Lead a large strategic Retail/CPG/Hospitality account, owning account strategy, growth, executive relationships, and delivery of data platforms, pipelines, governance, analytics, and AI solutions. Collaborate with Sales, Delivery, and partner ecosystems to ensure on-time, on-scope engagements and measurable business value.

Own territory growth in the Northeast by sourcing, co-selling with partner ecosystems, and closing enterprise data & AI services deals. Manage pipeline and forecasts, partner cross-functionally to scope and present solutions, ensure customer success, and exceed targets across Data Engineering, Managed Services, Machine Learning, and Analytics.

Lead activation and end-to-end delivery for Anthropic-focused accounts, build account plans and use-case backlogs, advise senior stakeholders on AI roadmaps, drive expansion, mentor team members, and contribute to internal playbooks to scale generative/agentic AI engagements.

Design, build, and productionize end-to-end cloud data solutions and pipelines. Translate business needs into data architectures, ensure performance, security, reliability, and scalability, lead technical reviews and client workshops, produce documentation and runbooks, mentor peers, and contribute reusable patterns, accelerators, and best practices for cloud data platforms.

Design and lead end-to-end applied AI architectures (predictive ML, MLOps, generative AI, LLMs, RAG, agentic workflows), translate business needs into production-ready solutions, prototype and deliver implementations, and ensure security, observability, governance, and operational reliability.

Partner with clients to define business goals and architect scalable Data & AI solutions, lead discovery and design, produce architecture diagrams and implementation plans, guide engineering teams through delivery to production, incorporate AI throughout the delivery lifecycle, and mentor engineers while advising executive stakeholders.

Lead end-to-end design, delivery, and lifecycle management of production AI/ML solutions for strategic clients. Translate business requirements into scalable, secure ML architectures, drive deployments, monitoring, governance, and mentor teams while collaborating with stakeholders across sales, engineering, and data science.

Client-facing architect role designing and delivering production Applied AI solutions (predictive ML, MLOps, generative AI, LLM apps, RAG, agentic workflows). Lead technical workstreams from discovery through production, advise on cloud/data/AI tech choices, ensure reliability, observability, governance, and support sales and delivery activities.

As a Machine Learning Solutions Architect, you will design and implement data solutions, provide thought leadership, and ensure scalable deployment of machine learning models.

Lead the development and operationalization of AI and Intelligence Platform strategies while advising C-suite on data and AI transformation. Shape offerings, support sales, and ensure successful delivery integration across teams.

Serve as executive-level technical leader and CTO-like advisor for strategic accounts: define architecture and roadmaps, drive delivery quality and expansion, mentor teams, align partners, and ensure client success and revenue growth.

Lead design and delivery of end-to-end data engineering solutions for enterprise clients. Architect cloud data platforms (Snowflake, AWS, Azure, Databricks, GCP), build and optimize SQL and transformation pipelines (dbt), mentor and manage solution architects and data engineers, produce technical documentation and presentations, and ensure production performance, security, scalability, and successful client engagement.

The Territory Director is responsible for scaling sales, building relationships with partners, sourcing new customers, and managing key accounts strategically within the Chicago region.

Drive delivery excellence and customer success by leading the architecture and implementation of AI/ML solutions while ensuring account growth and client engagement.

Lead design and delivery of end-to-end cloud data solutions, mentor solution architects and data engineers, engage clients, produce solution documentation and presentations, ensure performance, security, scalability, and CI/CD for production data platforms.

Lead architecture, operation, and continuous improvement of cloud-native, enterprise-scale data platforms (Snowflake, cloud storage, streaming). Translate requirements into roadmaps, design and optimize data warehouses and lakes, automate operations with Python and IaC, mentor engineers, and deliver managed services across multiple client accounts while driving reliability, security, and performance.

Lead design, implementation, and optimization of cloud-native data platforms (Snowflake, AWS, Azure) for managed-services clients. Translate business requirements into secure, scalable architectures, drive migrations and performance tuning, and provide hands-on technical leadership. Collaborate with cross-functional teams, mentor junior engineers, and contribute to best-practice frameworks, automation, and pre-sales efforts.

Own technical delivery and reliability of cloud-native data platform environments on AWS/Azure for managed clients. Implement and maintain IaC and CI/CD, monitor and resolve production pipeline issues, collaborate with architects and stakeholders, produce runbooks and documentation, mentor peers, and contribute reusable IaC and automation for Elastic Platform Operations.

Lead design, implementation, and optimization of cloud-native data platforms (Snowflake, AWS, Azure) for managed-services clients. Translate requirements into secure, scalable architectures, drive migrations, performance tuning, automation, monitoring, and mentor engineers while collaborating with sales, engineering, and executive stakeholders to maximize platform ROI and delivery excellence.