Data Analytics & AI Engineering Manager

JOB SUMMARY

The Data Analytics & AI Engineering Manager leads the design, development, and operationalization of data platforms, advanced analytics, and AI solutions within the ADAS organization. This role ensures alignment with the enterprise architecture, innovation roadmap, and managed services delivery model, enabling data-driven decision-making, automation, and scalable AI capabilities across business units.

The role bridges data engineering, analytics, and AI innovation, supporting both project-based delivery and managed services (L2/L3 support).

PRIMARY DUTIES & RESPONSIBILITIES:

1. Strategy & Capability Development

• Define and execute the Data, Analytics & AI capability roadmap aligned with ADS strategic goals
• Establish a capability maturity model (Foundational → Advanced → AI-driven enterprise)
• Collaborate with the Solutions Architecture & Innovation Office to align with enterprise architecture and emerging technologies
• Identify business opportunities (e.g., ADAS use cases in PH market) leveraging data and AI

1. Data Engineering & Platform Management

• Lead development of modern data platforms (data lakes, warehouses, lakehouse architectures)
• Ensure scalable and secure data pipelines (batch & real-time)
• Oversee data integration across ERP, EMR, and enterprise systems
• Implement data governance, quality, and metadata management frameworks

1. Analytics & Business Intelligence

• Deliver descriptive, diagnostic, predictive, and prescriptive analytics solutions
• Standardize BI dashboards and reporting frameworks (Power BI, Tableau)
• Enable self-service analytics capabilities across business units
• Translate business requirements into data models and insights

1. AI / Machine Learning Engineering

• Design and deploy machine learning and AI solutions (forecasting, NLP, computer vision, automation)
• Operationalize AI through MLOps frameworks (CI/CD for ML models)
• Ensure ethical AI practices, model governance, and explainability
• Drive AI adoption in managed services and enterprise applications

1. Delivery & Managed Services Integration

• Support ADAS delivery model (project + managed services)
• Establish L2/L3 support models for data platforms and AI solutions
• Define SLAs, OLAs, and performance metrics for analytics services
• Contribute to rate card definition and service packaging

1. Stakeholder & Business Engagement

• Partner with business leaders to identify high-value analytics and AI use cases
• Act as a translator between technical teams and business stakeholders
• Provide data-driven insights to support executive decision-making
• Support pre-sales and solutioning for new client opportunities

1. Team Leadership & Capability Building

• Build and lead a team of:

o Data Analysts / Engineers

o BI and Visualization Analysts

o Data Scientists / AI Engineers

o Data Governance & Quality Analysts

• Define roles, skillsets, and career pathways aligned with ADS structure
• Drive continuous learning (AI, cloud, data engineering tools)
• Foster a culture of innovation, experimentation, and quality delivery

Academic Qualification:

Bachelor’s or Master’s in Computer Science, Data Science, Engineering, or related field

Work Experience:

• 8–12 + years in data engineering, analytics, or AI roles
• 3–5 + years in leadership/management role
• Experience in enterprise-scale data platforms and AI deployments

Technical Expertise

• Data Engineering: SQL, Python, Spark, ETL/ELT tools
• Cloud Platforms: Microsoft Azure, Amazon Web Services, Google Cloud Platform
• BI Tools: Power BI, Tableau
• AI/ML Frameworks: TensorFlow, PyTorch, Scikit-learn
• Data Platforms: Snowflake, Databricks, Hadoop

Frameworks & Practices

• Data Governance (DAMA-DMBOK)
• MLOps / DevOps
• Agile / Scrum delivery
• TOGAF-aligned architecture practices

Leadership & Business Skills

• Strategic thinking and roadmap development
• Stakeholder management and communication
• Financial and cost optimization awareness (cloud & delivery)
• Pre-sales and solution design

Benefits:

• Company events
• Flexible schedule
• Health insurance
• Opportunities for promotion

Work Location: In person