Sr Data Engineer

About the role

The Signal Intelligence team at Paramount works with high-volume, multi-source data ecosystems to build trusted, decision-ready data products. They work across operational systems, client app event streams, ad tech platforms, stitcher events, ad server logs, and telemetry data to stitch these into data marts and dashboards that power business, product, and ad ops decisions.

Responsibilities

• Build and own data marts spanning operational, advertising, and telemetry data — designed for analytics, reporting, AI, and operational use cases
• Ingest and process large-volume event data from client apps, ad tech platforms, stitcher services, ad servers, and telemetry pipelines
• Clean, harmonize, and integrate data across systems with different schemas, identifiers, grains, and timing — producing conformed dimensions and shared definitions (users, sessions, devices, content, campaigns, impressions)
• Sew identity and sessions across client, server, and ad-side events to enable accurate user, content, and revenue analytics
• Debug data incidents end-to-end — from a dashboard anomaly back through marts, transformations, and raw event logs — and drive permanent fixes
• Develop and support visualizations in partnership with analysts and stakeholders, ensuring dashboards are accurate, performant, and trusted
• Establish data quality standards — testing, monitoring, alerting, freshness and volume SLAs — so issues are caught before stakeholders see them
• Document datasets, lineage, and business logic so consumers across analytics, product, and ad ops can self-serve with confidence
• Partner closely with analysts, data scientists, ad ops, product, and source-system owners to translate business questions into durable data models
• Develop/Improve new or underutilized data sets internally and externally
• Analyze complex and huge datasets to understand patterns and develop actionable insights
• Define new metrics and KPIs to track new initiatives
• Work closely with all business functions to enable transparent data-based decision making
• Contribute to the daily variance identification across multiple platforms
• Drive complex strategic projects investigations and analysis
• Work cross-functionally on enterprise-wide programs with Engineering, Broadcast Operations, Finance, BI and Data Engineering teams to improve performance and profitability
• Research and share information on the latest tools and best practices
• Mentor engineers and analysts on SQL, modeling, event data, and engineering best practices

Qualifications

• BA/BS in Computer Science, Math, Physics, Engineering, Economics, Statistics or related technical field
• 5+ years of data engineering experience building production pipelines and data models
• Expert SQL skills, including performance tuning on large, event-scale datasets
• Strong experience with a cloud warehouse / lakehouse (Snowflake, BigQuery, or Databricks)
• Experience working with JSON, Parquet, etc. types of files
• Proficient in Python for data processing and pipeline development
• Experience with dbt (or equivalent transformation framework)
• Experience with orchestration tools (Airflow)
• Hands-on experience with high-volume event data — clickstream, telemetry, ad impressions, or similar — including deduplication, late-arriving data, sessionization, and schema evolution
• Deep understanding of dimensional modeling, star/snowflake schemas, slowly changing dimensions, and data mart design
• Experience harmonizing data across multiple source systems with conflicting schemas, identifiers, or grain
• Comfort working directly with BI tools (DOMO, Looker, Mode) — both consuming them and supporting their development
• Strong analytical and logical skills

Bonus

• Attractive compensation and comprehensive benefits packages
• Generous paid time off
• Opportunities for both on-site and virtual engagement events
• Unique opportunities to make meaningful connections and build a vibrant community, both inside and outside the workplace