Senior Data Engineer
3 weeks ago
Senior Data Engineer
Location: Cleveland, OH
Industry: Retail
Overview
We have partnered with a manufacturing organization searching for a Data Engineer to join their growing team. The ideal candidate will have a strong background in managing and optimizing data pipelines, with expertise in various technologies and platforms. You will play a crucial role in designing, building, and maintaining our data infrastructure to support business intelligence, analytics, and machine learning initiatives.
Senior Data Engineer - Key Responsibilities:
- Design, develop, and maintain scalable data pipelines to ingest, transform, and load large volumes of data from diverse sources, ensuring data integrity and reliability.
- Utilize a combination of technologies to implement efficient ETL processes and data workflows.
- Implement partitioning, bucketing, and other optimization techniques to improve query performance and resource utilization in distributed computing environments.
- Collaborate with cross-functional teams to understand data requirements and develop solutions that meet business needs.
- Migrate and integrate data from on-premises systems to cloud platforms such as Databricks (Apache Spark) and AWS Glue, leveraging tools like Azure Data Factory for seamless data transfer.
- Ensure data quality and consistency by implementing data validation and monitoring processes, utilizing tools like Apache Spark, PySpark, and AWS Glue.
- Develop and maintain CI/CD pipelines to automate the deployment and testing of data pipelines and applications, ensuring reliability and efficiency in the software development lifecycle.
- Provide mentorship and guidance to junior team members, and conduct training sessions to educate developers on best practices in data engineering and CI/CD processes.
Senior Data Engineer - Qualifications
- Extensive development experience using Python and other scripting languages
- Expertise using Snowflake and incorporated data pipelines
- Expertise in ETL processes, data infrastructure, and pipeline development.
- Familiarity with DataOps, real-time data handling, automation, and CI/CD practices.
- Knowledge of cloud computing platforms, SQL databases, and big data tools such as Hadoop, Spark, or Kafka.
- Excellent written and oral communications skills
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