Cloud Support Engineer
1 day ago
Provide expert support for Databricks and AWS environments, ensuring smooth and efficient operation.
Monitor, troubleshoot, and resolve issues related to data pipelines, ETL processes, and data integration.
Develop, maintain, and optimize data pipelines using PySpark, Python and SQL.
Utilize Databricks components such as workflows, notebooks, jobs, Delta Lake, and Unity Catalog to manage and streamline data processes.
Collaborate with data engineers and analysts to ensure data accuracy and consistency across various systems.
Identify and implement performance improvements in existing data workflows and SQL queries.
Optimize storage and compute resources in Databricks and AWS to enhance efficiency and reduce costs.
Work closely with cross-functional teams, including data scientists, data analysts, and business stakeholders, to understand data requirements and provide technical solutions.
Document processes, procedures, and technical specifications for data engineering projects.
Document and implement best practices in data engineering, Databricks, AWS, PySpark, and SQL.
Participate in regular team meetings and contribute to the continuous improvement of data engineering practices and standards.
Roles & Responsibilities
Expertise in Databricks, including its various components such as Databricks Workflows, Databricks Notebooks, Databricks Jobs, Delta Lake, Unity Catalog, etc.
Expertise in AWS services, including S3, EC2, Lambda, Glue, MWAA, RDS and Redshift.
Strong proficiency in PySpark and SQL, with the ability to write and optimize complex queries and data transformation scripts.
Strong proficiency in any one of programming language Python/Java/Scala.
Experience with ETL processes and data pipeline development.
Minimum of 6-8 years of experience in a data engineering or data support role.
Proven track record of supporting and maintaining large-scale data systems and platforms.
Excellent problem-solving and analytical skills.
Strong communication and collaboration abilities.
Ability to work independently and manage multiple tasks simultaneously.
Relevant certifications in Databricks, AWS, or data engineering.
Experience with other big data technologies such as Hadoop, Spark, or Kafka is an added advantage.
Good to have data visualization tools and techniques exposure.
Years Of Experience
6 to 8 Years
Education/Qualification
BE / B.Tech / MCA / M.Tech / M.Com
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