Senior Data Analyst - AI
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Key skills for this role
About the Role
The role involves building scalable data pipelines, centralized reporting, and collaborating with teams on machine learning features and experimentation frameworks.
Key Skills for This Role
Responsibilities
- Build and maintain scalable, fault tolerant batch and streaming pipelines
- Define key metrics and build centralized reporting
- Design and own multi layer data models
- Engineer data flows for ML Feature Store
- Build pipelines and metrics frameworks for A/B testing
- Own ClickHouse as domain expert for schema design and performance tuning
- Implement CDC and event driven flows (e.g. Apache Kafka)
- Build and manage workflows with orchestration tools
- Define and interpret offline and online ranking metrics
- Partner with Data Scientists, ML Engineers, Product, and Backend teams
Requirements
- 4+ years as a Data/Analytics Engineer building data systems for analytics and ML
- Expert Python and advanced SQL
- Strong BI/visualization skills (e.g. Looker, Tableau)
- Hands on building pipelines with modern orchestration (Mage AI, Airflow, Prefect)
- Deep production experience with ClickHouse (or BigQuery, Snowflake, or similar)
- Hands on multi layer modeling (raw, staging, marts) using Kimball, Data Vault, or OBT patterns
- Solid grasp of experimentation frameworks
- Good grasp of the ML lifecycle and Feature Stores
Full Job Posting
Role Overview
- Own data and analytics across Gen AI and Recommendation Systems.
- Hybrid role: centralized reporting and building pipelines/data models.
- Define metrics for each product and partner with cross functional teams.
Key Responsibilities
- Build and maintain scalable, fault tolerant batch and streaming pipelines.
- Define key metrics and build centralized reporting.
- Design and own multi layer data models.
- Engineer data flows for ML Feature Store.
- Build pipelines and metrics frameworks for A/B testing.
- Own ClickHouse as domain expert.
- Implement CDC and event driven flows.
- Build and manage workflows with orchestration tools.
- Define and interpret offline and online ranking metrics.
- Partner with Data Scientists, ML Engineers, Product, and Backend teams.
Experience
- 4+ years as a Data/Analytics Engineer building data systems for analytics and ML.
- Expert Python and advanced SQL.
- Strong BI/visualization skills (e.g. Looker, Tableau).
- Hands on building pipelines with modern orchestration (Mage AI, Airflow, Prefect).
- Deep production experience with ClickHouse (or BigQuery, Snowflake, or similar).
- Hands on multi layer modeling using Kimball, Data Vault, or OBT patterns.
- Solid grasp of experimentation frameworks.
- Good grasp of the ML lifecycle and Feature Stores.
Nice to Have
- DBT for modeling and transformation.
- Building or integrating A/B platforms (e.g. Statsig, Optimizely, GrowthBook).
- Apache Kafka and CDC tools (e.g. Debezium, Maxwell).
- Graph Databases (e.g. Dgraph, Neo4j, Amazon Neptune).
- JavaScript or Go.
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