ProtoGene Consulting Private Limited

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

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