Ccube is looking for a skilled "AWS Data Engineer" to build and scale high-performance data pipelines and analytics platforms.
AWS Data Engineer
Location:Indore, MP (Hybrid 3 Days a Week)
Full Time
Experience: 5–10 Years
Key Skills Required:
Scala / Spark / Python
AWS Big Data (EMR, Airflow)
Strong Data Engineering concepts (ETL, Data Modeling, Data Lakes/Warehouses)
Redshift and/or Snowflake
SQL and performance optimization
What You’ll Do:
Design and develop scalable data pipelines
Work with big data frameworks and AWS services
Optimize data warehouses for analytics and reporting
Collaborate with data science and engineering teamsEducation
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience)
Competitive salary and benefits
Opportunity to work on large-scale cloud data platforms
Learning and growth opportunities in cutting-edge data technologies
Flexible work environment
📩 Interested candidates can apply/share resumes at "[email protected]"
Top Skills
What We Do
Driving Innovation through Advanced Data and AI Services.
We offer next-level data and AI services to help you transform your data into actionable insights for a competitive edge.
To augment your teams, we offer full-time/contract resources & consulting, design and development services for turnkey projects in the following areas:
01 DATA MODERNIZATION
Define Cloud strategy, architecture & roadmap
Identify current landscape & catalog data sources
Data warehouse design & setup
Develop data governance & data quality framework
Implement data management technologies
Build data analytics capabilities
Inculcate data driven culture
A future-ready framework to serve all business use cases
02 DATA INTEGRATION & CLOUD MIGRATION
Design & develop
Optimized data models and data pipelines
ETL/ELT workloads & monitoring
Processes that scale up and down without performance problems
Automate data migration between upstream/downstream (on-prem) systems and Cloud
03 DATA ANALYTICS & AI
Data analytics consulting – use-case exploration and building analytics roadmap
Data preparation and creating a single version of truth
Dashboard & report development
AI/ML model selection and development
AI/ML model tuning and validation
AI/ML model scaling, integration and deployment
