Lead Data Engineer – Experimentation

Eliassen Group; Santa Monica (CA); Hybrid; USD 114,000 - 128,000; Full time

Benefits offered by this job

Medical, Dental, Vision benefits

401k with company matching

Life insurance

Job summary

Eliassen Group is seeking a hands‑on Lead Data Engineer in Santa Monica, CA, with 7+ years building large‑scale data platforms. You will design and operate batch and real‑time pipelines using Spark, Kafka, and Databricks to power A/B tests and product analytics.

This hybrid role requires strong data modeling, governance, and collaboration with product and engineering teams. W2 role with a comprehensive benefits package including medical, dental, vision, 401k with company matching, and life

Qualifications

• 7+ years of data engineering with large-scale data platforms.
• Strong Python and SQL development.
• Expert-level Databricks and distributed processing experience.
• Deep knowledge of data modeling, ETL/ELT design, and data architecture.
• Experience with batch and real‑time streaming data pipelines, including Kafka and Spark Structured Streaming.
• Background in cloud-based data platforms and data warehousing or lakehouse technologies.
• Hands‑on experience with experimentation, A/B testing, product analytics, or analytics data platforms.
• Strong understanding of data quality, testing, governance, monitoring, and observability.

Responsibilities

• Design, develop, and maintain data infrastructure supporting A/B testing, feature launches, geo experiments, and product analytics.
• Build reusable frameworks and datasets to enable rapid, reliable experiment launch and measurement.
• Develop and operate large-scale batch and streaming pipelines using Spark, Kafka, and Databricks.
• Design scalable data models and data products for analytics, experimentation, and machine learning use cases.
• Implement monitoring, testing, validation, lineage, and governance frameworks to ensure trustworthy data.
• Partner with Product, Engineering, Data Science, and Business stakeholders to deliver scalable solutions.
• Influence architectural decisions and drive engineering best practices across teams.
• Mentor engineers and promote a culture of quality, innovation, and experimentation.

Skills

SQL

Python

Databricks

Data modeling

Streaming data

Kafka

Spark

Cloud platforms

A/B testing

Leadership

Tools

Databricks

Spark

Kafka

Job description

Description

Hybrid 4 Days a week on-site in Santa Monica, CA. Our client seeks a hands‑on Lead Data Engineer to build and scale experimentation data foundations that power product decisions across major streaming products. The role requires strong SQL, Python, Databricks, data modeling, and streaming expertise. The engineer will design and maintain batch and real‑time pipelines, implement data quality and governance, and partner with cross‑functional teams. The team values proactive communication, adaptability, and openness to AI tools and automation. Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

Rate: $83.00 to $93.00/hr. w2

Responsibilities

• Design, develop, and maintain data infrastructure supporting A/B testing, feature launches, geo experiments, and product analytics.
• Build reusable frameworks and datasets to enable rapid, reliable experiment launch and measurement.
• Develop and operate large-scale batch and streaming pipelines using Spark, Kafka, and Databricks.
• Design scalable data models and data products for analytics, experimentation, and machine learning use cases.
• Implement monitoring, testing, validation, lineage, and governance frameworks to ensure trustworthy data.
• Partner with Product, Engineering, Data Science, and Business stakeholders to deliver scalable solutions.
• Influence architectural decisions and drive engineering best practices across teams.
• Mentor engineers and promote a culture of quality, innovation, and experimentation.

Experience Requirements

• 7+ years of data engineering with large-scale data platforms.
• Strong Python and SQL development skills.
• Expert-level Databricks and distributed processing experience.
• Deep knowledge of data modeling, ETL/ELT design, and data architecture.
• Experience with batch and real‑time streaming data pipelines, including Kafka and Spark Structured Streaming.
• Background in cloud-based data platforms and data warehousing or lakehouse technologies.
• Hands‑on experience with experimentation, A/B testing, product analytics, or analytics data platforms.
• Strong understanding of data quality, testing, governance, monitoring, and observability.
• Proven experience leading technical initiatives and partnering with cross-functional teams.
• Excellent communication skills for technical and non-technical audiences.
• Nice to have: causal inference, statistical testing frameworks, ML data pipelines, feature engineering, CI/CD and infrastructure automation, media or subscription domains, and exposure to AI or agent-based solutions.