Data Engineer (Decision Science)

ViacomCBS; Newark (NJ); On-site; USD 80,000 - 120,000; Full time

Job summary

An established industry player is seeking a Data Engineer specializing in engagement and experimentation. This exciting role involves analyzing engagement metrics, optimizing personalization strategies, and developing real-time data processing solutions. You will collaborate with data scientists and product teams to ensure data accuracy and drive impactful decisions. With a focus on innovation, this position offers a collaborative environment where your contributions will shape the future of data analytics and personalization. If you're passionate about working with large-scale data and eager to make a difference, this opportunity is for you.

Benefits

Culture of learning

Collaborative team environment

Remote-friendly work setup

Qualifications

• 2+ years of experience as a Data Engineer with expert SQL skills.
• Strong analytical skills with a focus on A/B testing and data governance.

Responsibilities

• Design and maintain data pipelines for engagement metrics and A/B testing.
• Collaborate with teams to create scalable data solutions for personalized recommendations.

Skills

SQL

Data Analysis

Python/R

A/B Testing

Data Governance

Problem Solving

Education

Bachelor's Degree in Data Science or related field

Tools

BigQuery

Apache Superset

dbt (Data Build Tool)

Google Cloud Platform (GCP)

Looker

Job description

Overview and Responsibilities:

The Applied Intelligence Personalization Team at Paramount is looking for a Data Engineer - Engagement & Experimentation to join our team. This role will focus on analyzing engagement metrics, evaluating experiment results, and optimizing our recommendation and personalization strategies. The ideal candidate will be an expert in SQL, streaming data processing, and visualization tools like Apache Superset, ensuring that insights drive impactful decision-making.

Responsibilities Include:

1. Design and maintain data pipelines and analytics frameworks to track engagement metrics and A/B test results.
2. Build real-time data processing solutions to support personalized recommendations and content discovery.
3. Develop and optimize Superset dashboards and reports for experimentation insights and critical metric tracking.
4. Collaborate with data scientists, ML engineers, and product teams to translate business needs into scalable data solutions.
5. Ensure data accuracy, reliability, and performance in BigQuery and streaming data platforms.
6. Work with large-scale structured and semi-structured datasets, designing efficient SQL queries for analytics and reporting.
7. Automate ETL/ELT processes to ensure up-to-date data availability for decision-making.
8. Monitor and analyze A/B testing results to optimize personalization models and content recommendations.
9. Implement standard processes for data governance, quality, and documentation.

Key Projects:

1. Develop real-time engagement tracking and experimentation analysis pipelines.
2. Build Superset dashboards to monitor content recommendation performance.
3. Improve A/B testing frameworks for personalized user experiences.
4. Optimize streaming data workflows for user behavior analysis.
5. Improve SQL-based reporting to support data-driven decision-making.

Basic Qualifications:

1. 2+ years of experience as an Analytics Engineer or Data Engineer in a high-scale environment, along with expert-level SQL skills, experience in BigQuery or other cloud-based data warehouses, and proficiency in Python/R or other scripting languages for data manipulation.
2. Strong experience optimizing large-scale data queries and pipelines for performance and efficiency, along with experience building dashboards for visualization and reporting.
3. Strong analytical approach with experience in A/B testing frameworks and experimentation methodologies.

Additional Qualifications:

1. Strong communication skills to collaborate with ML engineers, data scientists, and product teams.
2. Hands-on experience with dbt (Data Build Tool) for transformation workflows.
3. Knowledge of data governance and quality standard processes.
4. Familiarity with Google Cloud Platform (GCP), BigQuery, and Looker.
5. Experience working with personalization and recommendation systems.
6. Strong problem-solving skills and a passion for working with large-scale data analytics.
7. Interest in open-source contributions and industry standard processes for analytics engineering.

What We Offer:

1. A culture of learning focused on innovation in data analytics and personalization.
2. A collaborative team environment where data drives decision-making.
3. A remote-friendly work setup with the opportunity to work on innovative engagement analytics and experimentation frameworks.

This role is a great opportunity to shape the future of personalization through advanced data analytics, experimentation, and real-time engagement tracking.

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