Verified Job
IT / Software / Data Analyst
Lead data engineer-Scala Expert
IT / Software / Data Analyst
#685518
Remote / WFH
Job Description
Job Title: Data Engineer (Scala, Spark, Pyspark, Databricks)
Remark - final round will be the F2F
Experience: 10+ Years (Lead Role)
Responsibilities
• Design, develop, and maintain robust and scalable data pipelines using Apache Spark and Scala on the Databricks platform.
• Implement ETL (Extract, Transform, Load) processes for various data sources, ensuring data quality, integrity, and efficiency.
• Optimize Spark applications for performance and cost-efficiency within the Databricks environment.
• Work with Delta Lake for building reliable data lakes and data warehouses, ensuring ACID transactions and data versioning.
• Collaborate with data scientists, analysts, and other engineering teams to understand data requirements and deliver solutions.
• Implement data governance and security best practices within Databricks.
• Troubleshoot and resolve data-related issues, ensuring data availability and reliability.
• Stay updated with the latest advancements in Spark, Scala, Databricks, and related big data technologies.
Required Skills And Experience
• Proven experience as a Data Engineer with a strong focus on big data technologies.
• Expertise in Scala programming language for data processing and Spark application development.
• In-depth knowledge and hands-on experience with Apache Spark, including Spark SQL, Spark Streaming, and Spark Core.
• Proficiency in using Databricks platform features, including notebooks, jobs, workflows, and Unity Catalog.
• Experience with Delta Lake and its capabilities for building data lakes.
• Strong understanding of data warehousing concepts, data modeling, and relational databases.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
• Experience with version control systems like Git.
• Excellent problem-solving and analytical skills.
• Ability to work independently and as part of a team.
Preferred Qualifications (Optional)
• Experience with other big data technologies like Kafka, Flink, or Hadoop ecosystem components.
• Knowledge of data visualization tools.
• Understanding of DevOps principles and CI/CD pipelines for data engineering.
• Relevant certifications in Spark or Databrick
Skills: lake,spark,scala,apache spark,big data technologies,apache,big data
Remark - final round will be the F2F
Experience: 10+ Years (Lead Role)
Responsibilities
• Design, develop, and maintain robust and scalable data pipelines using Apache Spark and Scala on the Databricks platform.
• Implement ETL (Extract, Transform, Load) processes for various data sources, ensuring data quality, integrity, and efficiency.
• Optimize Spark applications for performance and cost-efficiency within the Databricks environment.
• Work with Delta Lake for building reliable data lakes and data warehouses, ensuring ACID transactions and data versioning.
• Collaborate with data scientists, analysts, and other engineering teams to understand data requirements and deliver solutions.
• Implement data governance and security best practices within Databricks.
• Troubleshoot and resolve data-related issues, ensuring data availability and reliability.
• Stay updated with the latest advancements in Spark, Scala, Databricks, and related big data technologies.
Required Skills And Experience
• Proven experience as a Data Engineer with a strong focus on big data technologies.
• Expertise in Scala programming language for data processing and Spark application development.
• In-depth knowledge and hands-on experience with Apache Spark, including Spark SQL, Spark Streaming, and Spark Core.
• Proficiency in using Databricks platform features, including notebooks, jobs, workflows, and Unity Catalog.
• Experience with Delta Lake and its capabilities for building data lakes.
• Strong understanding of data warehousing concepts, data modeling, and relational databases.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
• Experience with version control systems like Git.
• Excellent problem-solving and analytical skills.
• Ability to work independently and as part of a team.
Preferred Qualifications (Optional)
• Experience with other big data technologies like Kafka, Flink, or Hadoop ecosystem components.
• Knowledge of data visualization tools.
• Understanding of DevOps principles and CI/CD pipelines for data engineering.
• Relevant certifications in Spark or Databrick
Skills: lake,spark,scala,apache spark,big data technologies,apache,big data
