Data Engineering Lead

Salary: ₱100,000 – ₱120,000 per month

Job Title: Head of Data Engineering

Department: Technology Department

Work Setup: Hybrid

Reports to: Chief Technology Officer (CTO) / Technology Leads

About the Role

As the Data Engineering Lead, you will spearhead the design, architecture, and scaling of our enterprise data platform. In the fast-paced online grocery ecosystem—where success hinges on real-time inventory tracking, predictive demand forecasting, lightning-fast order fulfillment, and optimized last-mile delivery across the Philippine archipelago—data is our core operational heartbeat.

You will lead a high-performing team of data engineers, database administrators, and analytics infrastructure specialists. Your mission is to build robust, secure, and scalable data pipelines that seamlessly connect supply chain systems, dark store/warehouse management tools, rider apps, and customer-facing mobile/web touchpoints into actionable, real-time insights.

Key Responsibilities

• Define and execute the company’s long-term data engineering roadmap, ensuring alignment with overall business objectives and rapid e-commerce growth.

• Design, build, and maintain scalable, resilient, and high-performance distributed data architectures (data lakes, data warehouses, and lakehouses) capable of handling massive transactional volumes.

• Modernize legacy data structures and introduce cutting-edge cloud infrastructure to optimize performance and reduce query latency.

• Oversee the end-to-end design, implementation, and automation of robust ETL/ELT pipelines.

• Implement real-time data streaming architectures (e.g., tracking live grocery inventory updates, stockouts, rider locations, and dynamic pricing changes).

• Ensure fault-tolerant data ingestion from disparate sources, including third-party merchant APIs, payment gateways, and logistics tracking tools.

• Lead, mentor, and scale the data engineering team, fostering a culture of technical excellence, continuous learning, and ownership.

• Manage hiring, resource allocation, capacity planning, and performance management for the department.

• Establish engineering best practices, code review standards, CI/CD automation, and rigorous documentation frameworks.

• Partner closely with Data Science and Analytics teams to feed clean, structured, and reliable data for machine learning models (e.g., demand forecasting, SKU recommendations, and route-optimization algorithms).

• Work hand-in-hand with Product, Software Engineering, and Operations/Supply Chain teams to ensure data instrumentation is embedded into new product features from day one.

• Champion data governance frameworks, ensuring data accuracy, consistency, integrity, and lineage across the organization.

• Enforce stringent data security practices and compliance policies, strictly adhering to the Data Privacy Act of 2012 (RA 10173) and other relevant regulatory guidelines in the Philippines.

Qualifications & Requirements

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, Information Technology, Statistics, or a related quantitative field.

• At least 8 years of total experience in software or data engineering, with at least 3 to 5 years in a leadership/management role (e.g., Data Engineering Manager or Head of Data).

• Proven track record in high-growth industries such as e-commerce, quick-commerce, fintech, logistics, or multi-branch retail, ideally within the Philippine market.

• Programming Languages: Advanced proficiency in Python, SQL, and Scala or Java.

• Big Data & Processing Frameworks: Deep hands-on experience with distributed data systems and frameworks such as Apache Spark, Hadoop, Kafka, or Flink.

• Cloud Platforms: Extensive experience architecting data solutions on major cloud environments (AWS, Google Cloud Platform (GCP), or Microsoft Azure).

• Data Warehousing & Modeling: Mastery of modern cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and dimensional modeling techniques (Star/Snowflake schema).

• Orchestration & DevOps: Familiarity with workflow management and CI/CD tools (e.g., Airflow, Dagster, dbt, Docker, Kubernetes).

What We Offer

1. Competitive Salary and Allowances

2. 30 Paid Leaves

3. HMO and Insurance Coverage

4. Flexible Work Schedule / Hybrid Work Setup

5. Annual Performance Increases