Lead Data Engineer | Python, SQL, Databricks | Santa Monica, CA

Location: Santa Monica, CA (Hybrid – 4 Days Onsite)

About the Opportunity: We're seeking an experienced Lead Data Engineer – Experimentation to join a leading media and streaming technology organization. In this role, you'll design and build scalable data platforms that power A/B testing, experimentation, product analytics, and data-driven decision-making across large-scale consumer streaming products. You'll work with Engineering, Data Science, and Product teams to transform massive volumes of user behavioral data into reliable, actionable insights that influence product strategy, customer engagement, personalization, and business growth. This is a highly technical, hands-on engineering opportunity for someone passionate about building large-scale data systems and enabling experimentation.

Key Responsibilities: Design, build, and maintain scalable data pipelines and distributed data platforms supporting experimentation and product analytics. Develop reliable batch and real-time streaming pipelines using Python, SQL, and modern data engineering technologies. Build data infrastructure supporting A/B testing, geo experiments, feature launches, and causal analysis. Design dimensional data models, analytical datasets, and data architectures optimized for experimentation and machine learning. Develop reusable frameworks and data products that enable teams to measure experiment outcomes accurately. Implement automated data quality checks, testing, monitoring, governance, and observability. Build and maintain production data systems with CI/CD and infrastructure automation. Collaborate closely with Data Scientists, Software Engineers, Product Managers, and business stakeholders. Provide technical leadership, architectural guidance, and mentorship to engineering teams.

Required Qualifications: 7+ years of experience in Data Engineering, Analytics Engineering, or large-scale data platforms, with a bachelor's degree in a related technical field. Strong hands-on programming experience with Python and SQL.Proven experience designing and operating large-scale data pipelines and distributed data systems. Strong understanding of ETL/ELT, data modeling, streaming architectures, and data warehouse/lakehouse technologies. Experience with cloud-based data platforms and technologies such as Databricks, Snowflake, Apache Spark, Kafka, or Airflow. Experience building data solutions for experimentation, product analytics, personalization, or machine learning. Strong knowledge of data quality, automated testing, monitoring, and governance. Ability to lead technical discussions and communicate effectively across engineering and business teams.

Preferred Qualifications: Experience building or supporting A/B testing platforms, experimentation infrastructure, or causal inference workflows. Experience with ML data pipelines, feature engineering, and model lifecycle systems. Experience with CI/CD, infrastructure automation, and production observability. Background in streaming media, subscription platforms, advertising technology, or consumer-facing digital products. Experience providing technical leadership, mentoring engineers, and influencing architecture decisions. Advanced degree in Computer Science, Engineering, Statistics, or a related quantitative discipline. Why This Opportunity? Work on high-scale data platforms supporting products used by millions of consumers. Build the data foundation for experimentation and product innovation. Solve complex engineering challenges involving massive datasets and distributed systems. Collaborate with talented engineers, data scientists, and product leaders. Make a measurable impact on customer experience, product development, and business strategy.