Looking for Technical Director / Technical Manager - ADMS, Data & AI

Job Description: Sr / Technical Director / Technical Manager - ADMS, Data & AI

Exp: 15 to 20 Years

Remote role

Role Overview:

The Technical Director - Data Engineering & AI provides strategic and technical leadership for the design, delivery, and scaling of enterprise-grade data platforms that power analytics and AI transformation across global clients. This role combines deep technical delivery experience with strategic vision, overseeing both Data Engineering and Application Development, Maintenance, and Support (ADMS) programs.

Reporting to the Global Head of Technology, the Director will lead large multi-geography teams, drive client success through Agile delivery excellence, and act as a trusted advisor to C-level executives. The ideal candidate comes from a strong IT services background with a proven record of delivering complex, large-scale data and application modernization initiatives.

Strategic Leadership & Delivery:

- Provide strategic direction and oversight for the Data Engineering and AI Solutions practice, driving business growth and technological innovation.

- Bring strong experience in technical delivery, having led Application Development, Maintenance, and Support (ADMS) projects across diverse technology environments.

- Lead large-scale, end-to-end delivery of enterprise data platforms and application programs using Agile and Scrum methodologies.

- Establish the technical vision and strategy for enterprise data platforms using both enterprise tools (Informatica, Talend, Snowflake) and open-source frameworks (Apache Spark, Kafka, Airflow, Hadoop).

- Define organizational standards for data architecture, ETL/ELT processes, and governance supporting AI and data-intensive applications.

- Develop cost optimization frameworks ensuring efficiency without compromising scalability and performance.

- Drive performance engineering and optimization initiatives to improve throughput and reduce latency across mission-critical pipelines.

- Foster close collaboration among Sales, Delivery, Data Science, and Solution Architecture teams to align enterprise data strategies with AI enablement.

- Build a Center of Excellence (CoE) for data engineering and delivery best practices, ensuring reliability, maintainability, and performance across all engagements.

- Oversee concurrent implementations of complex data infrastructures, including data lakes, warehouses, and real-time streaming solutions.

- Serve as a trusted advisor to clients on modernization, architecture, and AI-readiness strategy.

- Build, mentor, and scale globally distributed teams of data engineers, cloud architects, and DevOps specialists.

- Define and track KPIs, performance metrics, and data governance frameworks at an organizational level.

Business Development & Go-to-Market Strategy:

- Engage with C-level executives to understand strategic data and application challenges and articulate differentiated value propositions.

- Develop and execute go-to-market strategies for data engineering and AI solutions, identifying priority industries and target markets.

- Drive creation of thought leadership, service offerings, and IP assets to strengthen market presence.

- Review and approve complex architectures demonstrating AI-readiness and data modernization capabilities.

- Oversee proposal creation and client presentations showcasing advanced data and ADMS delivery frameworks.

- Partner with sales leadership to set revenue targets, develop account strategies, and close large-scale deals.

- Lead executive briefings and client meetings positioning the company as a leader in enterprise data and digital delivery.

- Own P&L responsibility for the practice, ensuring sustained growth across US and European markets.

Executive Client Relationship Management:

- Build and maintain strong relationships with CTOs, CIOs, CDOs, and senior data and technology leaders.

- Ensure high client satisfaction and successful delivery outcomes across strategic accounts.

- Serve as the escalation point for complex programs, driving proactive resolution and long-term partnership growth.

- Facilitate executive roundtables, industry events, and thought leadership forums to enhance the company's reputation as a trusted innovation partner.

Industry Domain Expertise:

- Apply deep understanding of data engineering and application delivery challenges in Retail, Telecommunications, BFSI, and Healthcare industries.

- Translate domain-specific requirements into scalable, compliant architectures supporting analytics and AI.

Example focus areas:

- Retail: Customer 360, personalization, supply chain optimization.

- Telecom: Network analytics, churn prediction, service optimization.

- BFSI: Fraud detection, risk modeling, regulatory reporting.

- Healthcare: Patient analytics, claims management, HIPAA compliance.

- Stay ahead of domain-specific technology and AI trends to inform client strategies.

- Build alliances with industry vendors and domain-focused technology partners.

Qualifications & Experience:

- Bachelor's or Master's in Computer Science, Data Engineering, or related discipline; MBA preferred.

- 15+ years of experience in technical delivery, data engineering, and distributed systems, with at least 5 years in a director-level leadership role.

- Proven track record in Application Development, Maintenance, and Support (ADMS) and large-scale Agile/Scrum project delivery.

- Strong experience delivering enterprise-scale programs in IT services environments for global clients (US & Europe).

- Expertise in enterprise data tools (Informatica, IBM DataStage, Talend, Snowflake, Databricks) and open-source frameworks (Hadoop, Spark, Kafka, Airflow).

- Proficiency with Python-based data ecosystems (pandas, NumPy, PySpark, Dask).

- Experience with production-grade orchestration (Airflow, Luigi, Prefect).

- Proven delivery of data pipelines integrated with AI/ML workflows.

- Strong understanding of cloud data architectures on AWS, Azure, or GCP.

- Experience in organizational data governance, cataloging, and quality frameworks.

- Demonstrated excellence in cost optimization, performance tuning, and platform scalability.

- Strong executive communication and stakeholder management skills.

- P&L ownership and proven business growth leadership.

- Extensive experience engaging with global enterprise clients (US and Europe).

Desirable Skills:

- Strategic understanding of AI/ML integration and MLOps frameworks.

- Leadership in establishing DataOps and continuous delivery practices.

- Familiarity with containerization (Docker) and orchestration (Kubernetes) for scalable workloads.

- Experience with regulatory compliance (GDPR, CCPA) in enterprise data management.

- Exposure to mergers or acquisitions within professional services.

- Strong understanding of Agile transformation and scaling Agile for distributed teams.

Key Success Metrics:

- Establish a high-performing Data Engineering & AI practice with robust delivery frameworks within 12 months.

- Deliver 2-3 large-scale modernization or ADMS programs annually.

- Achieve >95% client satisfaction across strategic accounts.

- Drive annual revenue growth of 25-30%.

- Reduce operational and infrastructure costs by >20% through optimization.

- Build and retain a globally distributed, high-performing technical team.

Core Competencies:

- Technical Delivery Leadership: Proven ability to lead large-scale data and application delivery in Agile environments.

- Strategic Vision: Translates enterprise goals into a cohesive data and AI roadmap.

- Client Leadership: Executive presence and advisory capabilities with C-suite stakeholders.

- Delivery Excellence: Drives high-quality execution across global delivery teams.

- Innovation: Promotes emerging technologies and accelerates AI-readiness.

- People Leadership: Builds, mentors, and scales technical talent across geographies.

- Commercial Acumen: Strong financial management and growth orientation.