Dear Professional
Greetings From Getinz!!
We are looking for Candidates who will be hand on Data Engineering Roles which the below Technologies Mentions.
Interested Candidates Can Drop Their Updated Resume which the below Mail Id Shared.
Please note:Immediate or serving Notice period will be preferable.
Azure DATA ENGINEERING:
– Prior experience in AWS services (Such as AWS Lambda, Glue, Step function, Cloud Formation, CDK)
– Knowledge of building bespoke ETL solutions
– Experience with Azure Data Factory
– Experience with Azure Data Lake Storage
– Experience with Azure Databricks with at least one of the following: Python/Pyspark Experience with Apache Spark
– Proficiency in SQL Database
– Proficiency in Azure Synapse Analytics
– Proficiency in building ETL data pipelines Strong Python and JavaScript skills
– Skills and proficiencies, we appreciate: Experience in Power BI
– Experience with ETL/ELT processes in the Azure cloud
– Ability to work effectively within Azure DevOps
– Azure Data certifications will be advantage –DP-203 Data Engineering Microsoft Azure certificationDP-900 Microsoft Azure Data Fundamentals certificationAZ-400 Designing and implementing Microsoft DevOps solutions certification
AWS
Key Responsibilities:
– Data Architecture: Design, develop, and maintain scalable and efficient data pipelines using AWS services (e.g., S3, Glue, Redshift) and Databricks.
– Databricks Implementation: Utilize Databricks for data processing, data manipulation, and transforming raw data into usable formats for analytics and reporting.
– Optimization: Optimize and fine-tune Databricks jobs, clusters, and workflows to ensure high performance, reliability, and cost-efficiency.
– Data Transformation: Transform and cleanse data using Databricks notebooks, leveraging Spark for large-scale data processing and manipulation.
– Integration and Automation: Integrate Databricks workflows with other AWS services and automate data processes to enable seamless data movement and analysis.
– Data Modeling: Implement data models and schemas suitable for analytics and reporting, ensuring data consistency and integrity.
– Monitoring and Troubleshooting: Monitor Databricks clusters and jobs, identify performance bottlenecks, and troubleshoot issues to ensure smooth data operations.
Skills and Qualifications:
– AWS Expertise: Proficiency in AWS services like S3, Glue, Redshift, EMR,
and understanding of AWS architecture for data solutions.
– Databricks Proficiency: Strong experience in using Databricks for data processing, Spark programming, and building efficient data workflows.
– Big Data Technologies: Knowledge of big data technologies and frameworks like Spark, Hadoop, and related ecosystems.
– Programming Skills: Proficiency in languages such as Python, Scala, or SQL for data manipulation and scripting within Databricks environments.
– Data Warehousing: Understanding of data warehousing concepts and experience in designing and implementing data warehouses.
– Problem-Solving: Ability to analyze complex data-related problems and propose effective solutions using Databricks and AWS services.
– Collaboration:
Strong teamwork and communication skills to collaborate with cross-functional teams and stakeholders.
Experience: Previous experience (5 to 7 years) in AWS-based data engineering roles with a focus on Databricks.
Education: Bachelor’s degree in Computer Science, Information Technology, or a related field. Relevant certifications in AWS or Databricks are a plus.
▶️ GBM-Data Engineer AWS/AZURE
🖊️ Getinz Techno Services
📍 Bengaluru
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