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Senior Data Engineer
3 weeks ago
Position Name : Sr Data Engineer
Experience Required : 8+years
Salary : As per the Market Standard or Else whatever budget you have
Notice period : Immediate joiner
Job Type : Full time
Location : Remote
Job Description :
Solution Architect (Databricks) :
Candidate having 8+ years of total experience in Data engineering (development/design), in which at least 5+ years as a Big Data architect/solution architect (on Big data platforms) , in which at least 3+ years of Proven experience as Architect/solution architect or a similar role on Databricks platform.
Excellent hands-on experience in architecting and implementing data processing, data warehousing, and data analytics solutions on the Aws Databricks platform having huge data volume, a variety of data types, for batch and real-time data ingestion.
Responsibilities :
- Enforce adherence to architectural standards/principles, global product-specific guidelines, usability design standards, etc.
- Proactively guide engineering methodologies, standards, and leading practices.
- Identify, communicate, and mitigate Risks, Assumptions, Issues, and Decisions throughout the full lifecycle.
- Provide guidelines in the definition of best practices & repeatable methodologies in Cloud Data Engineering, including Data Storage, ETL, Data Integration & Migration, Data Warehousing, and Data Governance
Required Skills :
- Must have 9+ years of experience in Data Engineering project development/design handling huge data, in which at least 5+ years on cloud using cloud data engineering services (preferably on aws)
- Must have designed and implemented at least 2-3 projects end-to-end in Databricks, E2E architecture of unified data platform covering all the aspect of data lifecycle starting from Data Ingestion, Transformation, Serve and consumption, understand composable architecture to take fullest advantage of Databricks capabilities.
- Must have Implemented and configured the Databricks environment, including clusters, notebooks, and libraries, ensuring optimal performance and resource utilization.
- Must have followed various architectural principles to design best suited per problem.
- Must have Designed and developed scalable designing both Batch and streaming data pipeline , data lake architectures, and data warehousing solutions on the Databricks platform using Spark and Delta Lake.
- Must be well versed with Databricks Lakehouse concept and its implementation in enterprise environments.
- Must have a strong understanding of Data warehousing and various governance and security standards around Databricks.
- Must have knowledge of cluster optimization and its integration with various cloud services, strong performance optimization skills to improve efficiency and reduce cost.
- Must be strong in writing unit test cases and integration test and Responsible to set best practices around Databricks CI/CD.
- Must have Integrated data from various sources, including structured, semi-structured, and unstructured data, into Databricks for processing and analysis.
(ref:hirist.tech)-
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