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:- PySpark, Amazon Web Services (AWS), SQL, AWS GLUE and Apache Airflow