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Paramount Global

Joint venture producing film, television content

Sr Data Engineer - Data Architecture and Modeling

Data EngineeringUpdated on Nov 14
Full-timeNew York, NY, USAIn-person

About the Job

Requirements

  • Expert SQL, including analytical SQL craft (window functions, complex joins, cohort, funnel, and sessionization logic) and performance tuning on large event-scale datasets.
  • Deep data-modeling expertise in dimensional modeling, star and snowflake schemas, slowly changing dimensions, conformed dimensions, grain, and data-mart design; ability to design a trusted source of truth from messy multi-source data.
  • Strong data analysis and business translation skills, including independently investigating data, defining metrics and key performance indicators, and turning ambiguous business questions into clear answers that enable others to self-serve.
  • Curiosity to learn the data terrain deeply, patience in helping non-technical partners, and communication that earns trust across the business.
  • Experience with dbt or an equivalent transformation or modeling framework.
  • Experience with a cloud warehouse; BigQuery is strongly preferred, and Snowflake or Databricks are acceptable with a fast ramp.
  • Python for data processing and pipeline development.
  • Orchestration experience with Airflow.
  • Experience with high-volume event data such as clickstream, telemetry, or ad impressions, including deduplication, late-arriving data, sessionization, and schema evolution.
  • A proven track record harmonizing data across multiple source systems with conflicting schemas, identifiers, or grain.
  • Comfort consuming and supporting BI tools such as DOMO, Looker, and Mode.
  • Experience debugging data-quality issues across the full stack, from BI tools to the warehouse to raw event logs.
  • A BA or BS in Computer Science, Math, Physics, Engineering, Economics, Statistics, or a related quantitative field.
  • Strong analytical and logical skills.
  • Experience with a semantic layer such as LookML, dbt Semantic Layer, or Cube is preferred.
  • Experience in streaming media or ad tech, including ad servers, SSAI or stitchers, VAST/VMAP, and impression and fill-rate metrics, is preferred.
  • Experience with streaming ingestion tools such as Kafka, Pub/Sub, or Kinesis is preferred.
  • Statistical analysis with R and predictive-analytics tooling, and experimentation or A/B analysis experience, are preferred.
  • Experience with master data management or entity resolution is preferred.
  • An MS in a quantitative discipline is preferred.

Responsibilities

  • Design and own dimensional and semantic models, including conformed dimensions, facts, star or snowflake schemas, slowly changing dimensions (Type 2), and well-defined grain, that serve as a trusted source of truth.
  • Architect data marts spanning operational, advertising, and telemetry domains for analytics, reporting, AI, and operational use.
  • Establish shared definitions and a semantic or metrics layer so users, sessions, devices, content, campaigns, and impressions have consistent meanings.
  • Write and optimize sophisticated analytical SQL, including window functions, cohort and funnel logic, sessionization, and distributions, on large event-scale datasets.
  • Analyze complex datasets to find patterns, quantify drivers, produce actionable insight, define new metrics and KPIs such as usage and revenue, and establish the logic behind them.
  • Independently investigate variance across platforms and communicate findings to peers and senior leadership.
  • Guide analysts and business partners through the data, explaining where numbers come from, what they mean, and their quirks and limitations.
  • Own and document institutional knowledge of data definitions, lineage, and metric reasoning so analysts, ad operations, product, and finance can self-serve with confidence.
  • Partner with stakeholders and source-system owners to translate ambiguous business questions into durable data models and metrics, and support or conduct strategic investigations and analysis.
  • Build and harmonize ingestion and transformation pipelines for event data from client apps, ad-tech platforms, stitchers, ad servers, and telemetry, handling deduplication, late-arriving data, sessionization, and schema evolution.
  • Stitch identities and sessions across client, server, and ad-side events for accurate user, content, and revenue analytics.
  • Establish data-quality standards, including testing, monitoring, alerting, freshness and volume service-level agreements, and troubleshoot incidents end-to-end from dashboard anomalies through marts, transformations, and raw logs.
  • Support and improve business intelligence dashboards; document datasets, lineage, and business logic to keep the data map trustworthy and current.
  • Mentor engineers and analysts on SQL, modeling, event data, and engineering best practices.

Desired Qualifications

  • Experience with a semantic layer such as LookML, dbt Semantic Layer, or Cube.
  • Experience in streaming media or ad tech, including ad servers, SSAI or stitchers, VAST/VMAP, and impression and fill-rate metrics.
  • Experience with streaming ingestion tools such as Kafka, Pub/Sub, or Kinesis.
  • Statistical analysis with R and predictive-analytics tooling, and experimentation or A/B analysis experience.
  • Experience with master data management or entity resolution.
  • An MS in a quantitative discipline.
  • Experience mentoring or leading engineers or analysts.

About the Company

Paramount Global

Joint venture producing film, television content

Preparing a concise company summary based on the provided description.

Company size
10,001+
Company stage
IPO
Headquarters
Los Angeles, CA
Founded
1912

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