Motion Recruitment | Jobspring | Workbridge

Data Analytics and Engineering Sr. Manager

Los Angeles, California

Hybrid

Full Time

$140k - $200k

We are currently seeking a Data Analytics and Data Engineering Manager for an exciting opportunity. This role will lead efforts in building and managing scalable data infrastructures and delivering actionable insights that drive business decisions. The ideal candidate has experience in both data analytics and engineering, and a background in fast-paced industries like e-commerce start-ups or health tech.

In this role, you will oversee a team of data engineers and analysts, working to optimize data pipelines, ensure data quality, and deliver key insights to stakeholders.

Required Skills & Experience:

  • Bachelor’s or Master’s degree in Data Science, Engineering, Analytics, or a related field.
  • At least 5 years of experience in data analytics and data engineering.
  • Proven experience managing teams of data professionals.
  • Strong expertise in building data pipelines using tools like Apache Spark, Databricks, or AWS Glue.
  • Proficiency in SQL, Python, and data visualization tools such as Tableau or PowerBI.
  • Deep understanding of cloud infrastructure (AWS, GCP, or Azure) for data storage and processing.
  • Background in e-commerce start-ups or health tech, with experience optimizing customer behavior, operations, or product insights.
  • Strong analytical skills and ability to turn data into actionable business strategies.

Desired Skills & Experience:

  • Experience with real-time data processing and streaming technologies.
  • Knowledge of data governance and data quality management.
  • Familiarity with data lake architectures and ETL processes.
  • Experience in developing predictive models or applying machine learning techniques in business contexts.

What You Will Be Doing:

Tech Breakdown:

  • 50% Data Pipeline and Infrastructure Management
  • 30% Data Analysis and Insights Generation
  • 20% Team Management and Collaboration

Daily Responsibilities:

  • 50% Overseeing Data Pipelines and Infrastructure
  • 30% Managing and Leading Data Teams
  • 20% Delivering Insights and Recommendations to Stakeholders

Posted by: Julie Bennett

Specialization: Data Engineering