Lead Data Engineer – Experimentation Platform

aKUBE

Lead Data Engineer at a tech services company developing data solutions for experimentation and A/B testing. Collaborating with Product, Engineering, and Data Science teams on strategic data initiatives.

Posted 7/3/2026contractSanta Monica • California • 🇺🇸 United StatesSenior💰 $100 per hourWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building scalable data platforms, with a strong focus on data engineering, cloud-based architectures, and data quality governance. Proficient in developing data pipelines and frameworks that support experimentation, analytics, and machine learning workloads.

Highest-signal resume keywords

Data EngineeringCloud-Based Data ArchitecturesPythonSQLCI/CD Implementation

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Hard Skills

Data ModelingETL/ELTDistributed Data ProcessingStreaming ArchitecturesData QualityData GovernanceBatch Data PipelinesStreaming Data PipelinesMachine LearningObservability

Soft Skills

MentoringCollaboration

Tools & Technologies

SparkDatabricksSnowflakeKafkaAirflow

Industry Keywords

Data PlatformsExperimentationA/B TestingAnalyticsPersonalization

Tech Stack

Tools & technologies

AirflowCloudETLKafkaPythonSparkSQL

About the role

Key responsibilities & impact

Design and build scalable data platforms supporting experimentation and A/B testing.
Develop batch and streaming data pipelines for large-scale user and product datasets.
Build reusable datasets and frameworks for experimentation, analytics, and product measurement.
Design dimensional data models and analytics-ready data products.
Implement automated data quality, validation, monitoring, lineage, and governance.
Build production-grade deployment pipelines with CI/CD and observability.
Partner with Product, Engineering, Data Science, and Analytics teams to deliver scalable data solutions.
Optimize data infrastructure supporting experimentation, personalization, and machine learning workloads.
Mentor engineers and establish best practices for large-scale data engineering.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related technical field.
7+ years of experience in data engineering or large-scale data platforms.
Strong experience with distributed data processing and cloud-based data architectures.
Hands-on experience with Python, SQL, Spark, Databricks, Snowflake, Kafka, and Airflow.
Strong understanding of data modeling, ETL/ELT, streaming architectures, and lakehouse concepts.
Experience building experimentation, analytics, personalization, or ML data platforms.
Experience implementing CI/CD, automated testing, monitoring, and data governance.
Strong system design and architecture experience.
Experience mentoring engineers and leading technical initiatives.

Benefits

Comp & perks

Work Authorization: GC, USC, All valid EADs except OPT, CPT, H1B