Data Engineer
Columbus, OH, United States
Responsibilities:
Develop and maintain ETL (Extract, Transform, Load) processes for efficient data integration.
Able to design and implement database schemas and write queries to retrieve and manipulate data.
Build and optimize efficient data pipelines and architectures.
Ensure data availability, integrity, and security.
Using scripting languages (e.g., Python, Bash) for automation of data workflows and processes.
Implementing containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes) for efficient deployment and management of data applications.
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements.
Requirements:
Bachelor’s/master’s degree.
Experience in data engineer role.
Proficiency in designing and implementing ETL processes to move and transform data (e.g., extracting data, data cleaning, joining data).
Proficient in at least one programming language, such as Python, Java, or Scala.
Proficiency in using SQL for data querying and manipulation.
Good understanding of database systems, both relational and NoSQL.
Good understanding of data warehousing and big data technologies, such as Hadoop, Spark, and Kafka, Amazon Redshift, Google BigQuery.
Knowledge on Apache Spark and PySpark.
Familiarity with AWS/Azure/GCP Cloud platform.
Familiar with concepts such as scalability, fault tolerance, and load balancing.
Good understanding of continuous integration/continuous delivery (CI/CD).
Knowledge of containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes).
PYTHON,JAVA,NoSQL
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