Senior Data Engineer

🔥 12 hours ago

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Logo of Paramount

Paramount

10,000+ employees

Founded 1912

📱 Media

👥 B2C

Media • B2C • Entertainment

Paramount is a global multimedia entertainment and news company that offers a range of services including direct-to-consumer digital subscription video on-demand and live streaming through Paramount+. It also owns Pluto TV, a leading free streaming television service, MTV, the world’s premier youth entertainment brand, and CBS Sports, a leader in television sports broadcasts. Paramount Pictures, since 1912, has been a legendary producer and distributor of films, hosting a library of over 1,000 titles. The company is deeply committed to inclusion and impact, focusing on diversity, global sustainability, and content that affects change. Being a significant player in both live and on-demand streaming services, Paramount embraces a wide array of content from sports to kids’ entertainment, comedy, and groundbreaking documentaries, impacting both linear and streaming platforms globally.

📋 Description

• 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) • Stitch identity and sessions across client, server, and ad-side events to enable accurate user, content, and revenue analytics • Troubleshoot data incidents end-to-end — from a dashboard anomaly back through marts, transformations, and raw event logs — and drive permanent fixes • Build, support and improve 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 o understand patterns and develop actionable insights o develop new initiatives to improve business KPIs such as usage, revenue, etc. o 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.

🎯 Requirements

• 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 • Proven track record harmonizing data across multiple source systems with conflicting schemas, identifiers, or grain • Experience debugging data quality issues across the full stack — from BI tool to warehouse to raw event logs • Comfort working directly with BI tools (DOMO, Looker, Mode) — both consuming them and supporting their development • Strong analytical and logical skills.

🏖️ Benefits

• medical • dental • vision • 401(k) plan • life insurance coverage • disability benefits • tuition assistance program • PTO • bonus eligible

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