Data Engineering Head

3 days ago

Pasig, National Capital Region, Philippines UnionBank of the Philippines Full time

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Direct message the job poster from UnionBank of the Philippines

Talent Attraction and Sourcing Officer | Sourcing for the best talents | Client Engagement and Solutions | Operations | Consumer Bank #OwnTheFuture

Job Description

· Define and implement the strategic vision for data engineering, ensuring alignment with the organization's data strategy and business goals.

· Lead, mentor, and develop a high-performing team of data engineers and data engineering leads. · Foster a culture of collaboration, innovation, and technical excellence within the team.

· Partner with senior executives, technology leaders, and business stakeholders to drive data initiatives.

· Establish and maintain key performance indicators (KPIs) to measure the success of data engineering initiatives.

Data Engineering & Architecture

· Oversee the design, development, and optimization of scalable ETL/ELT data pipelines, ensuring efficiency and data integrity.

· Ensure best practices in data ingestion, transformation, storage, and retrieval across various platforms (relational, cloud-based, and streaming).

· Drive adoption of modern data engineering frameworks and methodologies, including DataOps, CI/CD, and cloud-native architectures.

· Oversee data modeling and architecture design in collaboration with data architects to ensure seamless data flow across systems.

· Maintain compliance with data governance, security, and regulatory requirements.

Technology & Innovation

· Evaluate and implement cutting-edge technologies for data processing, cloud infrastructure, and real-time streaming.

· Guide teams in optimizing performance for data warehouses (Snowflake, Redshift, etc.) and streaming platforms (Confluent Kafka, Apache Flink, etc.).

· Promote automation of data processes using Python, SQL, and orchestration tools (Airflow, dbt, etc.).

· Ensure proper documentation and metadata management to support data lineage and traceability.

Collaboration & Business Engagement

· Work closely with data science, analytics, business intelligence, and governance teams to ensure seamless data integration.

· Partner with technology and infrastructure teams to optimize cloud and on-premise data solutions.

· Support data-driven decision-making by ensuring the availability of high-quality data for AI, ML, and advanced analytics initiatives.

Operational Excellence & Support

· Establish robust monitoring, alerting, and troubleshooting mechanisms for data pipelines and infrastructure.

· Oversee incident management, problem resolution, and root cause analysis (L3 support) to minimize downtime.

· Drive continuous improvement initiatives to enhance data availability, performance, and cost-efficiency.

· Manage budgets and resources effectively to ensure sustainable data operations.

Qualifications

  • Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field.
  • 10+ years of experience in data engineering, data architecture, or data management, with at least 5 years in a leadership role.
  • Deep expertise in SQL, Python, ETL/ELT development, and cloud-based data platforms (AWS, Azure, GCP, Snowflake, Redshift, etc.).
  • Strong experience with streaming data platforms (Confluent Kafka, Apache Flink, or similar).
  • Experience managing large-scale data infrastructure and pipelines with a focus on scalability, performance, and security.
  • Proven leadership experience in managing teams, mentoring engineers, and driving enterprise-wide data initiatives.
  • Strong understanding of data governance, metadata management, and regulatory compliance in the banking/finance sector.
  • Excellent communication, problem-solving, and stakeholder management skills.

Preferred Qualifications:

  • Experience with DataOps, CI/CD for data engineering, and infrastructure automation.
  • Familiarity with big data technologies such as Hadoop, Spark, or distributed computing frameworks.
  • Understanding of machine learning pipelines and AI-driven data processing.
  • Strong ability to drive cross-functional collaboration between data, IT, and business teams.
Seniority level
  • Executive
Employment type
  • Full-time
Job function
  • Information Technology, Engineering, and Management
  • Industries
  • Banking
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