Job Role : -Senior Data Engineer Job Location : -Metro Manila Experience : -8+ Years Role Overview Seeking an experienced Senior Data Engineer responsible for designing, developing, and optimizing scalable data warehousing and data platform solutions. The role involves end-to-end data architecture, pipeline development, platform migration, and cross-functional collaboration to support analytics and business decision-making. Ideal for candidates with strong Snowflake, Python, and cloud engineering expertise. Key Responsibilities: - Data Architecture & Engineering Design and implement scalable, high-performance data architectures using Snowflake, dbt, and Python . Build and maintain data warehouse layers including data foundation layers and data marts . Develop robust ETL/ELT pipelines for extracting, transforming, and loading data from diverse sources. Optimize data models and implement Medallion Architecture best practices. Manage data ingestion, storage, transformations, and delivery to analytics teams. Perform performance tuning , caching, and workload optimization across the data ecosystem. Data Platform Management Lead the migration of on-prem or legacy data platforms to Snowflake with minimal disruption. Manage full data lifecycle within Snowflakefrom ingestion to analytics. Troubleshoot and resolve environment-level issues and ensure high system availability. Automate manual processes and re-architect pipelines for scalability and efficiency. Cross-Functional Collaboration Work closely with product, analytics, design, and engineering teams to understand data needs. Support stakeholders by resolving data issues and ensuring data quality and integrity. Collaborate with technical and non-technical teams, translating business requirements into data solutions. Innovation & Continuous Improvement Explore emerging technologies such as Big Data, Machine Learning, Generative AI, and Predictive Modeling . Identify opportunities to improve data quality, processes, and system performance. Maintain coding standards, documentation, and best practices. Skills & Requirements: - Experience & Technical Expertise 8+ years of professional experience in Data Engineering. Strong programming skills, with hands-on Python expertise (must-have). Deep knowledge of Snowflake and experience designing cloud-based data solutions. Experience with dbt , SQL, and distributed data processing. Strong understanding of ETL/ELT concepts and pipeline development across databases, APIs, external data providers, and streaming sources . Proficiency with AWS, Azure, and/or GCP . Experience building and maintaining REST APIs for data workflows. Solid understanding of distributed systems , scalability concepts, and fault-tolerant architecture. Strong proficiency in both relational (SQL Server, Oracle, PostgreSQL, MySQL) and NoSQL databases. Strong analytical and root-cause analysis skills for structured and unstructured datasets. Soft Skills & Core Competencies Excellent communication skills, especially with non-technical stakeholders. Ability to explain insights and business narratives derived from data. Strong adherence to coding standards, governance, and data quality best practices. Demonstrated ability to evaluate and work with AI/ML and emerging technologies. Detail-oriented, proactive, and capable of working independently in a remote environment.