The Role
Leads the design and development of scalable batch and streaming data platforms for experimentation, A/B testing, analytics, personalization, and machine learning. Builds dimensional models, reusable datasets, data quality and governance systems, CI/CD pipelines, monitoring, and observability. Partners with product, engineering, data science, and analytics teams; optimizes cloud data infrastructure; mentors engineers; and establishes technical best practices.
Summary Generated by Built In
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: GC, USC, 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
- 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.
- 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.
- 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.
Skills Required
- 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, Apache Spark, Databricks, Snowflake, Apache Kafka, and Apache Airflow
- Strong understanding of data modeling, ETL/ELT, streaming architectures, and lakehouse concepts
- Experience building experimentation, analytics, personalization, or machine learning 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
- Experience with experimentation platforms or A/B testing infrastructure
- Causal inference or product analytics experience
- Machine learning feature engineering and model lifecycle pipeline experience
- Infrastructure automation and observability experience
- Subscription, streaming media, advertising, or consumer product experience
- Master's or PhD in a related technical field
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The Company
What We Do
Often, the biggest barrier between setting business objectives and achieving them is talent. Finding technically qualified people when you need them is hard enough. Finding technically qualified people who are the best fit for your organization is tougher. You need a staffing partner with the right expertise who can find the right talent in the right time frame, because your project can’t wait. That’s where we come in. aKube Inc is committed to leveraging its corporate values and operating model to achieve the highest level of performance and respect within the industry. We have developed a highly efficient delivery model for supporting a wide array of clients with expertise in supporting high-volume contingent worker programs.
