Jobs at phData

Designs, builds, deploys, and supports secure, scalable cloud data solutions and pipelines for enterprise clients. Translates business requirements into data architectures, integration patterns, and models; ensures performance, reliability, governance, and documentation. Provides technical leadership during reviews and workshops, collaborates with engineering and analytics teams, contributes reusable accelerators and best practices, mentors colleagues, and manages client engagements through delivery.

Leads Anthropic-focused AI consulting accounts from activation through delivery and expansion. Owns account plans, use-case backlogs, client roadmaps, delivery risk, executive relationships, and growth opportunities. Partners with sales, delivery, marketing, and Anthropic teams to turn pilots into multi-phase AI transformation programs. Requires strong consulting, account growth, AI/data, scoping, and stakeholder leadership experience, with travel up to 50%.

Design and implement end-to-end cloud data solutions, lead or mentor engineering teams, ensure performance, security, and scalability, integrate diverse data sources, write and optimize SQL, program in Java/Python/Scala, produce presentations and detailed solution documentation, and engage directly with clients to deliver production-ready systems.

Leads complex, client-facing data and AI programs from strategy through delivery. Responsibilities include managing roadmaps, scope, budgets, margins, risks, forecasting, change control, executive communications, partner coordination, and measurable outcomes. The role orchestrates multi-geo teams, coaches delivery professionals, manages stakeholder relationships, and improves delivery methodologies across consulting engagements.

Design, build, and deploy secure, scalable cloud data solutions and pipelines for enterprise clients. Translate business requirements into architectures, integrations, and data models; ensure production performance and reliability; lead technical reviews and workshops; create reusable documentation and accelerators; and collaborate with distributed engineering, analytics, platform, and client teams. The role also includes mentoring, delivery ownership, stakeholder communication, and contributing to consulting practice excellence.

Lead client discovery, architect scalable enterprise Data and AI solutions, and guide engineering teams through production delivery. Serve as a technical advisor, create architecture documentation and implementation plans, manage technical risks, apply AI throughout the software lifecycle, mentor engineers, and communicate recommendations to technical and executive stakeholders.

Lead IT operations to ensure reliability, security, and performance of cloud systems, end-user devices, and collaboration platforms. Provide end-to-end employee support, administer identity, endpoint and device management, drive migrations and automation, manage IT asset governance, participate in audits, and cover rotational shifts and weekend on-call duties to support a global workforce.

Lead executive discovery, process and value-stream analysis, and requirements definition for data, AI, and GenAI transformations. Facilitate workshops, identify automation opportunities, define data and model requirements, support pilots and UAT, manage stakeholder alignment, and measure business outcomes. Serve as a trusted client advisor, use generative AI to accelerate business analysis, ensure deliverable quality, and coach project team members.

Lead client discovery and executive engagement to identify high-value AI and data opportunities. Translate ambiguous business problems into use cases, hypotheses, MVP scopes, business cases, and measurable KPIs. Facilitate workshops, prototype solutions using AI-assisted and low/no-code tools, and partner with technical teams to develop scalable solutions. Manage client alignment, scope, risk, adoption, and change communication while connecting technology investments to business value.

Designs and delivers end-to-end data engineering solutions for enterprise clients, including production implementation, data integration, SQL optimization, cloud data platforms, automated transformation, orchestration, testing, deployment, and documentation. The role also requires client-facing communication, technical presentations, solution roadmaps, proof-of-concept development, and collaboration to ensure performance, security, scalability, and reliability.

Leads client discovery, architecture, and delivery of enterprise Data and AI solutions from initial design through production deployment. Advises executives and technical stakeholders on platforms, tooling, trade-offs, and AI adoption; guides engineering teams, manages technical risks, creates architecture documentation, and mentors engineers. Requires deep cloud, data engineering, AI, consulting, and modern software delivery expertise.

Leads AI and data product management engagements across client portfolios, owning delivery quality, scope, financial performance, roadmaps, and adoption KPIs. Manages staffing, recruiting, utilization, and team performance while driving go-to-market strategy, pipeline, revenue, presales, and consulting engagements. Establishes product management standards, AI-assisted workflows, and reusable delivery frameworks, partnering with executive stakeholders to scale products from MVP to production.

Leads complex client-facing data and AI programs from strategy through delivery, coordinating multi-geo teams and partners. Owns roadmaps, budgets, margins, risks, escalations, utilization, change control, and executive communications. Partners with technical leaders to connect delivery with measurable business outcomes, identifies account expansion opportunities, and supports coaching and AI-augmented delivery practices. The role requires managing multiple customers and workstreams across cloud, analytics, data platforms, and AI/ML environments.

Advise enterprise clients on AI and data strategies, transformation roadmaps, operating models, governance, privacy, technology rationalization, and business cases. Lead discovery workshops, executive engagements, and art-of-the-possible sessions; prioritize use cases and connect technical recommendations to business outcomes. Build the advisory practice, develop offerings, manage multidisciplinary teams, mentor staff, strengthen client and partner relationships, and support successful distributed project delivery.

Lead end-to-end architecture and hands-on delivery of production-ready agentic AI solutions for enterprise clients. Design reusable accelerators, reference architectures, evaluation and guardrail strategies, and cloud-native deployments. Translate ambiguous business needs into scalable, secure, observable systems while collaborating with engineers, data scientists, platform teams, and stakeholders. Mentor team members, establish delivery standards, support consulting engagements, and advise senior clients on AI roadmaps and strategic initiatives.

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

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.

Leads phData’s Anthropic private equity vertical, owning commercial strategy, fund and portfolio-company relationships, AI value-creation frameworks, engagement origination, and client outcomes. Translates Claude and broader data and AI capabilities into measurable EBITDA improvement, operational efficiency, and exit readiness. Builds scalable playbooks, account plans, financial models, and multi-year programs while partnering with Anthropic field teams and mentoring delivery leaders.

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.

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.