Senior Analytics Engineer - AI & Data Modeling
Engineering Airflow SQL Data Warehousing Data Engineer SPARK
Salary
Location
Benefits
13th month salary
Laptop/desktop for works
Other benefits
Work-from-home
Job Overview And Responsibility
About the Role We're looking for a Senior Analytics Engineer to build the data foundations that power AI-driven business intelligence. You'll design semantic layers, metrics frameworks, and data models that enable both business users and AI systems to extract insights from production data. This role combines traditional analytics engineering (dbt, SQL, data modeling) with emerging AI capabilities (LLM integration, natural language analytics). You'll work at the intersection of data engineering, business intelligence, and AI—building the intelligent data layer that makes complex analytics accessible through natural language. If you love building clean data models and want to explore how AI can transform how people interact with data, this role is for you. - Design and maintain analytical data models and transformations using dbt, SQL, and modern data stack tools - Build semantic layers (metrics, dimensions, business definitions) that translate raw data into business concepts - Create metrics frameworks and dimensional models (star schemas, fact tables, dimension tables) - Integrate semantic layers with LLM-powered analytics agents for natural language querying - Develop metadata retrieval systems that ground AI reasoning in your data models - Collaborate with AI/ML teams to evolve analytics capabilities into intelligent, multi-step workflows - Ensure data quality, lineage, and governance across analytical datasets
Required Skills and Experience
- 4+ years experience in data engineering or analytics engineering with strong data modeling focus - Can translate business requirements into maintainable data models - Advanced SQL - complex queries, optimization, analytical schema design - Hands-on dbt experience (or similar: Spark, Airflow, Dagster) - Strong understanding of dimensional modeling (star schema, fact/dimension tables, SCDs) - Experience building semantic layers, metrics frameworks, or BI data models - Worked with modern data warehouses (Snowflake, BigQuery, Databricks, Redshift)
Why Candidate should apply this position
- Competitive package - Hybrid working model - Macbook Pro provided for work - Bonus: 13th month salary - Weekly learning sessions and offsites - Close-knit small team culture
Preferred skills and experiences
- Python proficiency for data pipelines and automation - Exposure to LLMs or AI-driven analytics (natural language querying, automated insights) - Knowledge of data governance, lineage tracking, and quality frameworks - Experience with BI tools (Looker, Tableau, Mode, Hex) - Interest in AI/ML and willingness to learn (we'll teach you!) - Strong communication skills with business stakeholders
Report to
Chief Digital Officer
Interview process
Overview interview -> Technical interview (90mins) -> Fit interview (in English)
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