Top Tech Jobs & Startup Jobs

Supports executives and stakeholders in defining business problems, requirements, processes, and success metrics for data, AI, and digital transformation initiatives. Identifies automation opportunities, specifies AI and data requirements, facilitates workshops, supports pilots and change management, partners with technical teams, oversees UAT, and maintains client relationships. Uses generative AI to accelerate analysis and documentation while validating outcomes and coaching project teams.

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.

Lead complex client-facing AI and data programs from strategy through delivery, coordinating multi-geo teams and partners. Own roadmaps, budgets, margins, risks, escalations, client relationships, and measurable business outcomes. Partner with technical leaders, provide executive reporting, identify account expansion opportunities, and coach project managers and consultants. The role requires strong program management experience in consulting or professional services, familiarity with modern data and AI platforms, and willingness to travel up to 50% per month.

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.

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.

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

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.

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.

Lead operation, reliability, and continuous improvement of cloud data platforms (streaming, lakes, warehouses). Provide architecture and hands-on operational support, collaborate cross-functionally, drive automation, mentor engineers, and act as trusted advisor for enterprise clients.