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Lead Data Engineer - Experimentation Platform - 1633

Santa Monica, CA, US • Posted 1 hour ago • Updated 1 hour ago

Full Time

On-site

USD 100.00 per hour

Fitment

Dice Job Match Score™

🎯 Assessing qualifications...

Job Details

Skills

Employment Authorization
Apache Airflow
Data Warehouse
Data Quality
Product Engineering
Data Science
Computer Science
Mathematics
Statistics
Data Engineering
Data Processing
Cloud Computing
Python
SQL
Apache Spark
Databricks
Snow Flake Schema
Apache Kafka
Data Modeling
Extract
Transform
Load
ELT
Continuous Integration
Continuous Delivery
Automated Testing
Data Governance
Systems Design
Mentorship
A/B Testing
Analytics
Machine Learning (ML)
Streaming
Advertising

Summary

Job Description
City:Santa Monica, CA

Onsite/ Hybrid/ Remote: Hybrid (4 days onsite per week, no flexibility)

Duration: 6Months

Rate Range: Upto $100/hr on W2

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

Must Have:

Python
SQL
Data Engineering
ETL / ELT
Apache Spark
Databricks
Snowflake
Apache Kafka
Apache Airflow
Streaming Data Pipelines
Data Modeling
Data Warehousing / Lakehouse
A/B Testing / Experimentation Platforms
CI/CD for Data Pipelines
Data Quality & Data Governance
Cloud Data Platforms

Responsibilities:

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.

Qualifications:

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.

Nice to Have:

Experimentation platforms or A/B testing infrastructure.
Causal inference or product analytics experience.
ML feature engineering and model lifecycle pipelines.
Infrastructure automation and observability.
Subscription, streaming media, advertising, or consumer product experience.
MS or PhD in a related technical field.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: RTX1d3dc7
Position Id: 6b0bf17860ad473e72f299ce7fa07c55
Posted 1 hour ago

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