AI Data Engineer

We are hiring an AI Data Engineer who is strong on the data side and hands-on with AI. You will own our data pipelines end to end, reconciling messy operational data, modelling it cleanly, and turning it into dashboards, alerts, and reports that the operations team acts on daily, and building AI/ML features on top of that data. You will work directly with our CTO with a lot of ownership.
Responsibilities:
Build and maintain data pipelines on Databricks (medallion bronze/silver/gold) over Azure.
Reconcile and clean multi-source operational exports into one trustworthy, well-modelled dataset.
Write robust SQL and Python for transformations, validation, and automation.
Build performance dashboards and analytics (Metabase / BI) that operations leads use daily.
Build real-time alerting, monitoring, and automated reporting into the tools the team already uses.
Own data-driven workflows such as driver performance/payroll/settlement pipelines and external-data automation (e. g., public-data integrations).
Build and support AI/ML features, predictive models, and LLM-powered automation on top of your data.
Requirements:
Strong SQL and Python.
Databricks / Spark and Azure cloud, with medallion / bronze-silver-gold pipeline experience.
Solid data engineering: ETL, reconciliation, data modelling, data quality, Docker.
Machine learning fundamentals (scikit-learn): predictive models such as late delivery or performance scoring.
LLM / AI agents and automation.
With a strong analytics mindset, you turn raw data into clear dashboards and insights.
Clear written English and meaningful daily overlap with US business hours.
Time-series forecasting.
BI tools (Metabase, Power BI) and messaging/automation integrations (e. g., WhatsApp Business API).
Last-mile, logistics, or operations-domain experience.

Experience
2-4 yrs