ProtoGene Consulting Private Limited
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The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Data Engineer + Integration engineer + Support specialistExp – 5-8 years
Necessary Skills:· SQL & Python / PySpark
· AWS Services: Glue, Appflow, Redshift
· Data warehousing
· Data modelling
Job Description:· Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform. Design/ implement, and maintain the data architecture for all AWS data services
· A strong understanding of data modelling, data structures, databases (Redshift), and ETL processes
· Work with stakeholders to identify business needs and requirements for data-related projects
Strong SQL and/or Python or PySpark knowledge
· Creating data models that can be used to extract information from various sources & store it in a usable format
· Optimize data models for performance and efficiency
· Write SQL queries to support data analysis and reporting
· Monitor and troubleshoot data pipelines
· Collaborate with software engineers to design and implement data-driven features
· Perform root cause analysis on data issues
· Maintain documentation of the data architecture and ETL processes
· Identifying opportunities to improve performance by improving database structure or indexing methods
· Maintaining existing applications by updating existing code or adding new features to meet new requirements
· Designing and implementing security measures to protect data from unauthorized access or misuse
· Recommending infrastructure changes to improve capacity or performance
Experience in Process industry
Data Engineer + Integration engineer + Support specialistExp – 3-5 years
Necessary Skills:· SQL & Python / PySpark
· AWS Services: Glue, Appflow, Redshift
· Data warehousing basics
· Data modelling basics
Job Description:· Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform.
· A strong understanding of data modelling, data structures, databases (Redshift)
Strong SQL and/or Python or PySpark knowledge
· Design and implement ETL processes to load data into the data warehouse
· Creating data models that can be used to extract information from various sources & store it in a usable format
· Optimize data models for performance and efficiency
· Write SQL queries to support data analysis and reporting
· Collaborate with team to design and implement data-driven features
· Monitor and troubleshoot data pipelines
· Perform root cause analysis on data issues
· Maintain documentation of the data architecture and ETL processes
· Maintaining existing applications by updating existing code or adding new features to meet new requirements
· Designing and implementing security measures to protect data from unauthorized access or misuse
· Identifying opportunities to improve performance by improving database structure or indexing methods
· Designing and implementing security measures to protect data from unauthorized access or misuse
· Recommending infrastructure changes to improve capacity or performance
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Skills / Tools
- SQL & Python / PySpark
- AWS Services: Glue, Appflow, Redshift - Mandatory
- Data warehousing basics
- Data modelling basics
Job Description
- Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform. Design/ implement, and maintain the data architecture for all AWS data services
- A strong understanding of data modelling, data structures, databases (Redshift), and ETL processes
- Work with stakeholders to identify business needs and requirements for data-related project
- Strong SQL and/or Python or PySpark knowledge
- Creating data models that can be used to extract information from various sources & store it in a usable format
- Optimize data models for performance and efficiency
- Write SQL queries to support data analysis and reporting
- Monitor and troubleshoot data pipelines
- Collaborate with software engineers to design and implement data-driven features
- Perform root cause analysis on data issues
- Maintain documentation of the data architecture and ETL processes
- Identifying opportunities to improve performance by improving database structure or indexing methods
- Maintaining existing applications by updating existing code or adding new features to meet new requirements
- Designing and implementing security measures to protect data from unauthorized access or misuse
- Recommending infrastructure changes to improve capacity or performance
- Experience in Process industry
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