Lead the architecture design and end-to-end development of amodern, cloud-native data platformon Snowflake, aligned withLakehouse architecture principles.
Design, implement, and ownhigh-performance ETL/ELT pipelines, ensuring scalability, reliability, and reusability.
Build and optimizedata models(star schema, normalized models) to support analytics, BI, and machine learning workloads.
Collaborate closely withData Scientists and AI Engineersto deliver training data pipelines, model inference layers, and agent-ready data services.
Manage the integration ofstructured and unstructured data sources, ensuring robust data governance, security, and compliance standards.
Promote best practices incode quality, documentation, testing, and CI/CDacross the data engineering function.
Mentor junior and mid-level engineers, perform code reviews, and foster a culture of technical excellence.
Engage directly with global product and business stakeholders inEnglish, including requirement analysis, solution design, and architectural presentations.
Contribute to the development ofAI-driven data services and intelligent agents, leveraging real-time data and vector-based retrieval.
Driveperformance optimization, cost efficiency, and infrastructure scalabilityacross the data platform.
REQUIREMENTS
5+ yearsof hands-on experience in data engineering or large-scale data platform development.
Proven, in-depth expertise withSnowflake, including platform architecture, performance tuning, cost optimization, and ELT pipeline design.
Advanced proficiency inPython and SQL, with the ability to deliver production-grade, efficient code.
Solid experience building and orchestrating ETL/ELT workflows usingAirflow, dbt, or similar tools.
Strong understanding ofLakehouse architecture, data warehousing concepts, and large-scale performance optimization.
Hands-on experience with at least one majorcloud platform(AWS, Azure, or GCP).
ExcellentEnglish communication skills, both written and verbal, with the ability to work effectively with international stakeholders and senior leaders.
Strong leadership, analytical thinking, and project execution capabilities.
Nice to have
Experience across theAI/ML lifecycle, including MLOps or AI agent integration (vector databases, embeddings, etc.).
Hands-on experience withreal-time or streaming data pipelines(Kafka, Kinesis, etc.).
Familiarity withLLM and AI frameworkssuch as LangChain, OpenAI/Gemini APIs, HuggingFace, or similar tools.
Knowledge ofdata governance frameworks, including data cataloging, lineage, and privacy management.
Background inhigh-growth environments, particularly AI-focused startups or global technology organizations.
Benefits
Full salary during probation period
Comprehensive healthcare coverage, including annual health check-ups and premium medical insurance
Annual leave entitlement plus public holidays
Performance-based bonus reviews are conducted twice per year
Project-based performance incentives
Annual company trip and team outings upon project completion
