Lead Data Engineer

1 week ago

Manila, National Capital Region, Philippines Aboitiz Data Innovation (ADI) Full time

Hybrid - Manila 3-5 Yrs Exp Bachelor Full-time

Job Description

Aboitiz Data Innovation (ADI) is one of the leading up and coming start-ups in the field of Data Science and Artificial Intelligence. We believe data can drive change for a better world by advancing businesses across industries and communities.

We are seeking a highly skilled Lead/Senior Data Engineer to architect, develop, and optimize data pipelines and infrastructure supporting analytics, machine learning, and business intelligence initiatives. This role will serve as a primary source of knowledge, ensuring the seamless integration of complex data systems within an industrial environment, with a particular focus on power plant control systems, data historians, financial systems, and asset management platforms. The ideal candidate must possess advanced technical expertise and strong stakeholder management skills to lead cross-functional collaborations and drive data-driven decision-making within the power generation and energy sector.

Responsibilities and DutiesTechnical Leadership & Data Architecture
  • Design, implement, and maintain highly scalable, resilient, and efficient data architectures for on-premise, hybrid, and cloud-based solutions.
  • Drive the selection and development of engineering methods, tools, and techniques aligned with the Software Development Lifecycle (SDLC) and industry best practices.
  • Establish data governance and security standards to ensure compliance with regulatory frameworks and organizational policies.
  • Develop and maintain high-performance data storage solutions, optimizing for analytics, machine learning, and predictive modeling.
  • Oversee data lineage, cataloging, and metadata management to enhance data discoverability and usability.
Advanced Data Processing & Pipeline Optimization
  • Lead the end-to-end design and automation of structured and unstructured data pipelines, ensuring efficiency, reliability, and scalability.
  • Architect and implement real-time and batch data processing frameworks, leveraging tools such as Apache Spark, Kafka, and Airflow.
  • Integrate diverse data sources, including power plant control systems, IoT sensors, data historians, enterprise applications, and financial systems.
  • Implement machine learning model operationalization (MLOps) in collaboration with data scientists and AI engineers.
  • Establish data observability mechanisms to proactively monitor data quality, lineage, and pipeline health.
Stakeholder Engagement & Cross-Team Collaboration
  • Act as the primary liaison between business stakeholders, engineers, data scientists, UX designers, and executive leadership to align data initiatives with business objectives.
  • Facilitate discussions to translate business requirements into technical solutions, ensuring alignment with operational goals.
  • Drive strategic process improvements, optimizing data accessibility, governance, and quality.
  • Present data-driven insights and architecture recommendations to senior leadership and decision-makers.
  • Lead technical mentoring programs, providing guidance to junior and mid-level data engineers.
  • Identify and champion emerging technologies to enhance data engineering capabilities and future-proof infrastructure.
  • Conduct continuous research and development (R&D) to improve data management, integration, and processing techniques.
  • Spearhead initiatives to leverage advanced analytics, AI, and IoT-driven insights for optimizing power generation efficiency.
  • Develop technology roadmaps for scaling data infrastructure to support evolving business needs.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
  • 8+ years of experience in data engineering, with at least 3 years in a leadership or senior role.
  • Expertise in SQL, Python, R, and distributed computing frameworks (Spark, Hadoop, Kafka, etc.).
  • Proven experience in designing and implementing cloud-native and hybrid data architectures (AWS, Azure, or Google).
  • Strong background in ETL/ELT pipeline development, data modeling, and orchestration (Airflow, Prefect, Dagster Cloud, etc.).
  • Deep understanding of data governance, security, and compliance frameworks.
  • Excellent interpersonal, communication, and stakeholder management skills.
  • Experience in power generation, energy, or industrial data management is a strong plus.
Preferred Qualifications
  • Experience with data mesh, data fabric, or federated data architectures.
  • Advanced knowledge of graph databases, time-series databases, and NoSQL solutions.
  • Familiarity with MLOps, DataOps, and DevOps principles.
  • Prior experience working with SCADA systems, industrial IoT, or operational technology (OT) data.
  • Strong public speaking and presentation skills to influence executive decision-making.
Working Location

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