| PySpark Developer with Data Bricks at Remote, Remote, USA |
| Email: [email protected] |
| From: SHASHI, Cloudingest [email protected] Reply to: [email protected] PySpark Developer with Data Bricks Remote Job Description :: Develop and optimize data processing jobs using PySpark to handle complex data transformations and aggregations efficiently. Design and implement robust data pipelines on the AWS platform, ensuring scalability and efficiency(Databricks exposure will be an advantage) Leverage AWS services such as EC2, S3, etc. for comprehensive data processing and storage solutions. Expertly manage SQL database schema design, query optimization, and performance tuning to support data transformation and loading processes. Design and maintain scalable and performant data warehouses, employing best practices in data modeling and ETL processes. Utilize modern data platforms for collaborative data science, integrating seamlessly with various data sources and types. Ensure high data quality and accessibility by maintaining optimal performance of Databricks clusters and Spark jobs. Develop and implement security measures, backup procedures, and disaster recovery plans using AWS best practices. Manage source code and automate deployment using GitHub along with CI/CD practices tailored for data operations in cloud environments. Provide expertise in troubleshooting and optimizing PySpark scripts, Databricks notebooks, SQL queries, and Airflow DAGs. Keep abreast of latest developments in cloud data technologies and advocate for the adoption of new tools and practices that can benefit the team. Use Apache Airflow to orchestrate and automate data workflows, ensuring timely and reliable execution of data jobs across various data sources and systems. Collaborate closely with data scientists and business analysts to design data models and pipelines that support advanced analytics and machine learning projects. Qualifications: Bachelors or Masters degree in Computer Science, Engineering, Information Technology, or related field. Minimum of 5 years of experience as a Data Engineer with extensive expertise in AWS, and PySpark. Deep knowledge of SQL and experience with data warehouse design and optimization. Strong understanding of AWS services and how they integrate with Databricks and other data engineering tools. Demonstrated ability to design, build, and maintain end-to-end data pipelines. Excellent problem-solving abilities, with a track record of implementing complex data solutions. Nice to Have :: Experience in managing and automating workflows using Apache Airflow. Familiarity with Python, Snowflake, and CI/CD processes using GitHub. Strong communication skills for effective collaboration across technical teams and stakeholders. Keywords: continuous integration continuous deployment sthree PySpark Developer with Data Bricks [email protected] |
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| Wed Jul 03 23:31:00 UTC 2024 |