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AI/MLData Analytics Hybrid

Senior AI Analytics Engineer

Job Overview

As a Senior AI Analytics Engineer in our Data Team, you will bridge the gap between Data Engineering, Tech, and Product. In addition to core analytics engineering, you will occasionally act as a technical Business Analyst on select data initiatives—partnering with business teams to translate ambiguous operational needs into clear technical specs and data requirements.

Key points

  1. Design, build, and maintain production-grade data models to bridge raw data streams with downstream applications and BI tools. Using LLMs and AI tools to…

  2. Standardize data modeling practices and build robust, reliable, scalable semantic layers that feed clean, trustworthy data to downstream analytics and reporting.

  3. Business & Requirements Analysis: Occasionally lead scoping discussions with product, tech and finance stakeholders to translate business requirements into functional specs, user stories…

  4. Reconciling data definitions across departments, a critical human-led task that AI cannot fully automate.

  5. Hands-on expertise with modern data transformation and orchestration frameworks (dbt, Airflow, Prefect, Dagster).

  6. Deep experience with cloud data warehouses (Snowflake, Databricks, BigQuery).

  7. Understanding of feature engineering, AI agentic workflow lifecycles, and evaluation metrics.

  8. Experience with deploying AI agentic workflows in production environments.

Skills

Advanced SQL capabilitiesSQLLLMsStakeholder ManagementPythonCI/CDGitETL

Experience: Senior-level · 5+ years · Job type: Full-time

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