2 часа назад
Senior Principal Data Engineer (Databricks/MLOps)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Principal Data Engineer (Databricks/MLOps): Architecting a unified MLOps and forecasting platform for campaign projections, lift analysis, and budget forecasting with an accent on Databricks, MLflow, real-time data processing, and scalable model deployment. Focus on building automated pipelines, implementing incrementality testing, productionizing prediction models, and establishing CI/CD and telemetry standards for high-scale advertising systems.
Location: Remote, US
Company
operates a purchase intelligence and incentives platform that helps businesses attract, understand, and incentivize consumers through digital reward programs.
What you will do
- Architect a unified MLOps and forecasting platform on Databricks using MLflow, Databricks SQL, and Unity Catalog.
- Build automated pipelines for campaign-performance forecasting, real-time budget utilization prediction, and incrementality testing.
- Establish CI/CD, deployment, data quality, telemetry, and debugging standards for scalable production models.
- Analyze large datasets to improve model performance and advertising outcomes.
- Partner with Applied Scientists on GenAI patterns and automated architectures.
- Translate business goals into technical roadmaps and mentor senior and staff engineers.
Requirements
- 10+ years of data engineering experience, including substantial experience building and scaling production MLOps pipelines.
- Expertise with the Databricks Data Intelligence Platform, Unity Catalog, and MLflow.
- Proficiency in Python, SQL, and PySpark, with deep knowledge of data modeling and semantic-layer design.
- Strong understanding of time-series forecasting, statistical modeling, or causal inference.
- Experience leading large-scale architectural migrations and managing technical debt.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field; PhD preferred.
Nice to have
- Experience integrating ranking, retrieval, and conversion models into high-traffic marketplace funnels.
- Experience with real-time systems and large-scale processing technologies such as Kafka or Kinesis.
- Familiarity with Learning to Rank models and productionization challenges.
- Experience implementing AI-powered assistants for product development, alert triage, or workload migration.
Culture & Benefits
- Flexible paid time off and company holidays.
- Medical, dental, and vision insurance from the first day.
- 401(k) retirement plan with company match and a student loan repayment option.
- Employee Stock Purchase Plan and educational assistance.
- Lifestyle Spending Account and Calm app subscription for wellbeing support.
- MacOS is the preferred platform, with Windows also supported; Google Workspace is used across the organization.
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