Data Engineer at Motion Recruitment
Los Angeles, CA 90001
About the Job
Los Angeles, CaliforniaHybridFull Time$140k - $200kWe are seeking an experienced Data Engineer with a focus on building robust data systems to support digital advertising platforms
In this role, you will design and maintain scalable data pipelines, process large volumes of real-time and batch data, and support cross-functional teams in deriving insights from data
The ideal candidate has expertise in data engineering and a strong understanding of the tools necessary for handling complex, high-velocity datasets commonly found in the advertising ecosystem.This position requires hands-on experience with cloud technologies, data frameworks, and real-time processing solutions to ensure data accuracy, scalability, and performance.Required Skills & Experience:Bachelor’s or Master’s degree in Data Engineering, Computer Science, or related field
At least 5 years of experience in data engineering, including building and optimizing ETL processes
Strong proficiency in Python, Java, or Scala for data processing and pipeline development
Experience with distributed data processing frameworks such as Apache Spark, Apache Beam, or Hadoop
Expertise in real-time data processing using tools like Apache Kafka, AWS Kinesis, or Google Pub/Sub
Proficiency with cloud platforms like AWS (Redshift, S3, Glue), Google Cloud (BigQuery, Dataflow), or Azure (Data Lake, Synapse)
Strong SQL and NoSQL skills for building and optimizing data stores (e.g., PostgreSQL, Cassandra, DynamoDB)
Familiarity with containerization and orchestration tools such as Docker and Kubernetes
Experience automating data workflows with Airflow, Prefect, or similar orchestration tools.Desired Skills & Experience:Experience managing and processing high-volume datasets in advertising, e-commerce, or similar domains
Knowledge of data lakes, data warehouses, and building architectures that support both structured and unstructured data
Familiarity with batch and real-time data integration techniques
Experience in implementing and maintaining CI/CD pipelines for data applications
Knowledge of machine learning pipelines and integrating models into data systems
Strong understanding of data security, governance, and compliance best practices.What You Will Be Doing:Tech Breakdown:50% Building and Optimizing Data Pipelines 30% Real-Time Data Processing and Integration 20% Collaboration with Data Science and Engineering TeamsDaily Responsibilities:60% Hands-On Data Engineering and Development 20% Building and Optimizing ETL Processes 20% Monitoring, Debugging, and Reporting on Data SystemsPosted by: Julie BennettSpecialization: Data Engineering
In this role, you will design and maintain scalable data pipelines, process large volumes of real-time and batch data, and support cross-functional teams in deriving insights from data
The ideal candidate has expertise in data engineering and a strong understanding of the tools necessary for handling complex, high-velocity datasets commonly found in the advertising ecosystem.This position requires hands-on experience with cloud technologies, data frameworks, and real-time processing solutions to ensure data accuracy, scalability, and performance.Required Skills & Experience:Bachelor’s or Master’s degree in Data Engineering, Computer Science, or related field
At least 5 years of experience in data engineering, including building and optimizing ETL processes
Strong proficiency in Python, Java, or Scala for data processing and pipeline development
Experience with distributed data processing frameworks such as Apache Spark, Apache Beam, or Hadoop
Expertise in real-time data processing using tools like Apache Kafka, AWS Kinesis, or Google Pub/Sub
Proficiency with cloud platforms like AWS (Redshift, S3, Glue), Google Cloud (BigQuery, Dataflow), or Azure (Data Lake, Synapse)
Strong SQL and NoSQL skills for building and optimizing data stores (e.g., PostgreSQL, Cassandra, DynamoDB)
Familiarity with containerization and orchestration tools such as Docker and Kubernetes
Experience automating data workflows with Airflow, Prefect, or similar orchestration tools.Desired Skills & Experience:Experience managing and processing high-volume datasets in advertising, e-commerce, or similar domains
Knowledge of data lakes, data warehouses, and building architectures that support both structured and unstructured data
Familiarity with batch and real-time data integration techniques
Experience in implementing and maintaining CI/CD pipelines for data applications
Knowledge of machine learning pipelines and integrating models into data systems
Strong understanding of data security, governance, and compliance best practices.What You Will Be Doing:Tech Breakdown:50% Building and Optimizing Data Pipelines 30% Real-Time Data Processing and Integration 20% Collaboration with Data Science and Engineering TeamsDaily Responsibilities:60% Hands-On Data Engineering and Development 20% Building and Optimizing ETL Processes 20% Monitoring, Debugging, and Reporting on Data SystemsPosted by: Julie BennettSpecialization: Data Engineering