Lead Data Engineer

Responsibilities
1. Data Platform Architecture & Infrastructure
● Own the technical direction and scalability of Company streaming and batch infrastructure, keeping pace with rapid data growth.
● Optimize data models, query performance, and storage across our lake and warehouse ecosystems to balance performance with compute costs.
2. Core Identity & Pipeline Engineering
● Architect high-throughput, fault-tolerant ETL pipelines using a Medallion framework to progressively refine raw signals into analytics-ready datasets.
● Design and scale our identity graph capabilities, unifying fragmented consumer traits, visitor leads, and customer identities into a singular, highly dependable product.
ML Data Engineering & MLOps Collaboration
● Build and maintain feature pipelines and feature stores that power our predictive AI/ML models (e.g., identity resolution, propensity scoring).
● Partner directly with Data Science to operationalize models, assisting with production deployments, scaling, and retraining workflows.
Data Governance & Engineering Excellence
● Define platform-wide data governance protocols, including ownership, data lineage, cataloging, access controls, and compliance.
● Champion engineering best practices by establishing robust frameworks for data quality, CI/CD testing, and pipeline observability.
Qualifications
● 8+ years of professional Data Engineering experience with a proven track record of leading technical projects or mentoring junior/mid-level engineers.
● Strong programming skills in Python (familiarity with [protected info] is a plus).
● Expert command of SQL and data modeling across large-scale analytical systems.
● Deep production experience with large-scale cloud data ecosystems (AWS: S3, Kinesis, Athena, Redshift, Lambda; or equivalent GCP: BigQuery, Dataflow, Pub/Sub, Cloud Storage).
● Proven execution using ClickHouse (or a comparable columnar/OLAP database engine) at scale.
● Hands-on experience orchestrating data workflows with Airflow (or an equivalent framework).
● Hands-on mastery of lakehouse design concepts, specifically implementing Medallion data layering.
● Exposure to building data pipelines that support ML/AI workflows (feature pipelines or feature stores).
● Strong English communication skills, with experience working effectively in a distributed, multi-country engineering environment.
Bonus Skills
● Experience in MarTech/AdTech, particularly working with identity resolution, first-party cookie data, ordigital marketing platforms.
● A strong technical footprint or interest in Data Science / MLOps frameworks.
● Prior experience thriving in a fast-paced, high-ownership, early-to-mid stage B2B SaaS environment.
🔗 Apply: [protected info]
📩 CV: [protected info]
📱 Contact: [protected info] (Ms. Nhan)