Analytics Engineer Manager, CNBC & MS NOW

VersantEnglewood Cliffs, NJ
Hybrid

About The Position

We’re looking for a strategic and technically strong Manager, Analytics Engineering to scale our data foundation. This role will lead the evolution of our Databricks environment, building high-quality datasets and forecast models that power insights across audience, content, and revenue. You’ll partner closely with analytics and data engineering teams to improve how data is structured, defined, and used, setting standards for modeling, quality, and documentation. Your work will ensure analysts can work directly in the warehouse with confidence, accelerating insight generation and raising the technical bar across the team.

Requirements

  • 5 years of experience in analytics engineering, data analytics, or a related field
  • Strong expertise in SQL and working in modern data platforms (e.g. Databricks)
  • Experience building and maintaining data models across bronze/silver/gold layers (or equivalent)
  • Proven ability to define and enforce data quality, testing, and documentation standards
  • Experience developing forecasting or statistical models (e.g., for traffic, revenue, or subscriptions)
  • Strong understanding of how analysts use data, with a passion for improving self-service and scalability
  • Ability to balance hands-on technical work with enablement and mentorship of others
  • Excellent collaboration skills, with experience partnering with data engineering and cross-functional teams

Responsibilities

  • Own and evolve the teams Databricks environment, creating clear and scalable structures
  • Partner with data engineering to enhance upstream (silver-layer) data models and pipelines
  • Ensure data is reliable, performant, and aligned with business definitions
  • Set standards for data modeling, QA, and documentation
  • Coach and support analysts in writing production-quality SQL and building transformations
  • Build forecasting and modeling frameworks for digital traffic and subscriber forecasting
  • Partner with analytics and business teams to prioritize high-impact data investments

Benefits

  • medical, dental and vision insurance
  • 401(k)
  • paid leave
  • tuition reimbursement
  • a variety of other discounts and perks
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