
Global media and entertainment company
Senior Lead Data Engineer, Content Engineering at Paramount
About the role
#We Are Paramount on a mission to unleash the power of content… you in?
We’ve got the brands, we’ve got the stars, we’ve got the power to achieve our mission to entertain the planet – now all we’re missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter – both for our audiences and our employees – and aim to leave a positive mark on culture.
Overview
We are hiring a Senior Lead Data Engineer to build and scale the data foundations that power Paramount’s next-generation personalization systems across Home, Search/Browse, Notifications, and Artwork. This role sits at the core of the Content Engineering vertical, partnering closely with Applied ML, ML Platform, and Causal Science teams to deliver highly reliable, ML-ready data at global scale. You will design and operate pipelines processing billions of daily events, petabyte-scale feature stores, and real-time engagement streams that support ranking and recommendations. This is a high-impact role for an engineer who thrives in distributed systems, large-scale ETL/streaming, and delivering production-grade infrastructure aligned with cutting-edge personalization.
Why This Role Matters
Paramount is investing heavily in a unified personalization operating model. In this role, you will directly shape:
- The Data Backbone: Building the core of our personalization ecosystem.
- The User Experience: Defining the feature sets that identify what millions of users view.
- Innovation Velocity: Enabling ML teams to innovate quickly and safely through high-quality experimentation data.
Key Responsibilities
- Build & Operate Large-Scale Feature Pipelines: Design and maintain batch/streaming pipelines (Spark, Flink, Databricks, Airflow) producing ML features for ranking models.
- Ensure Point-in-Time Correctness: Develop feature sets that enable unbiased offline training and credible online inference.
- Develop Embedding & Content Pipelines: Build scalable workflows for metadata, imagery, and multimodal representations; partner with Science teams to operationalize new models.
- Architect Data Foundations: Design Delta/Parquet data models and medallion layers, optimizing storage layout and partitioning for latency and cost.
- Real-Time Engineering: Build Kafka-based systems for real-time features and user-activity aggregations, ensuring robust handling of out-of-order events and exactly-once semantics.
- Governance & Leadership: Define data quality rules and schema evolution processes while collaborating across ML pods to translate model needs into infrastructure.
Basic Qualifications
- 7+ years of experience in large-scale data or software engineering.
- Hands-on Expertise: Deep experience with Spark (Py Spark/Scala), Databricks, Airflow, and Kafka.
- ML Data Modeling: Proficiency in feature pipelines, temporal joins, and mitigating training-serving skew.
- Cloud Ecosystems: Experience with AWS/Azure/GCP and high-performance engines like Snowflake or Redshift.
- Technical Foundations: Proficient programming skills in Python and SQL with a focus on performance optimization.
Additional Qualifications
- Experience in personalization domains (search, ranking, or recommender systems).
- Experience supporting petabyte-scale data lakehouses or feature stores.
- Familiarity with GenAI/RAG systems, multimodal content, or Delta Live Tables.
- Knowledge of Causal Inference, experimentation signals, or ML evaluation workflows.
- Experience with Terraform for governed, repeatable deployments.
What Success Looks Like
In your first 6–12 months, you will:
- Take Ownership: Manage critical feature and content pipelines powering personalization across multiple surfaces.
- Drive Efficiency: Improve feature freshness and reliability while reducing pipeline latency and cost.
- Set Standards: Introduce new monitoring and governance practices that elevate engineering across the AMLG.
- Technical Leadership: Become the go-to expert for distributed systems and ML data infrastructure within Content Engineering
Paramount Streaming, a division within Paramount Global, is the home to the company's direct-to-consumer services spanning free and paid in the form of Pluto TV and Paramount+. Pluto TV is the global leader in free ad-supported TV, delivering more than 1,400 global channels and an extensive library of streaming content, including live and original channels. Paramount+, digital subscription video-on-demand and live streaming service, combines live sports, breaking news, and A Mountain of Entertainment™. Paramount+ features an expansive library of original series, hit shows and popular movies across every genre from world-renowned brands and production studios, including SHOWTIME®.
ADDITIONAL INFORMATION:
Hiring Salary Range: $156,800.00 - 235,200.00.
The hiring salary range for this position applies to New York, California, Colorado, Washington state, and most other geographies. Starting pay for the successful applicant depends on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education. The benefits available for this position include medical, dental, vision, 401(k) plan, life insurance coverage, disability benefits, tuition assistance program and PTO or, if applicable, as otherwise dictated by the appropriate Collective Bargaining Agreement. This position is bonus eligible.
What We Offer:
- Attractive compensation and comprehensive benefits packages. Check out our full list of benefits here: https://www.paramount.com/careers/benefits
- Generous paid time off.
- An exciting and fulfilling opportunity to be part of one of Paramount’s most dynamic teams.
- 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.
- Explore life at Paramount: https://www.paramount.com/careers/life-at-paramount
Paramount is an equal opportunity employer (EOE) including disability/vet.
At Paramount, the spirit of inclusion feeds into everything that we do, on-screen and off. From the programming and movies we create to employee benefits/programs and social impact outreach initiatives, we believe that opportunity, access, resources and rewards should be available to and for the benefit of all. Paramount is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, and Veteran status.
If you are a qualified individual with a disability or a disabled veteran, you may request a reasonable accommodation if you are unable or limited in your ability to use or access https://www.paramount.com/careers as a result of your disability. You can request reasonable accommodations by calling 212.846.5500 or by sending an email to paramountaccommodations@paramount.com. Only messages left for this purpose will be returned.
Required skills
Data engineering
ETL
Streaming pipelines
Distributed systems
Feature stores
Real-time data processing
Platform reliability
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About Paramount

Paramount
PublicParamount Skydance Corporation is an American multinational mass media and entertainment conglomerate.
51-200
Employees
Abu Dhabi
Headquarters
$8B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
3.2
Compensation
3.5
Culture
4.1
Career
2.8
Management
2.4
65%
Recommend to a friend
Pros
Good benefits and compensation
Supportive and friendly team environment
Flexible work arrangements
Cons
Poor management and leadership
Limited growth and advancement opportunities
High workload and stress
Salary Ranges
74 data points
Mid/L4
Senior/L5
Mid/L4 · Data Engineer
2 reports
$145,555
total per year
Base
$111,966
Stock
-
Bonus
-
$145,555
$145,555
Interview experience
6 interviews
Difficulty
3.0
/ 5
Duration
14-28 weeks
Offer rate
83%
Experience
Positive 50%
Neutral 50%
Negative 0%
Interview process
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
Panel Interview
5
Offer
Common questions
Behavioral/STAR
Past Experience
Culture Fit
Industry Knowledge
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