This role requires a blend of strategic architecture expertise and hands-on engineering capabilities to transform complex data into actionable business insights while ensuring security, scalability, governance, and cost optimization.Experience Required
- 5+ years of overall experience in Data Engineering.
- 2+ years of hands-on experience in AWS Data Architecture and Cloud Data Platforms.
- Proven experience designing and implementing enterprise-scale data solutions.
- Amazon S3
- Amazon Redshift
- AWS Glue
- Amazon EMR
- Amazon Kinesis
- AWS IAM
- Advanced proficiency in:
- Python
- Scala
- Java
- Expertise in distributed computing frameworks such as:
- Apache Spark
- Hadoop
- Flink
- AWS Lake Formation
- Experience with:
- Terraform
- AWS CloudFormation
- Version control using Git.
- Deployment automation using tools such as:
- Jenkins
- GitHub Actions
- AWS CodePipeline
- AWS Certified Solutions Architect.
- Databricks
- Snowflake
At Ccube, we strive to create a supportive and growth-oriented work environment. Our employee value proposition includes:
Dynamic Work Culture
Career Growth
Learning & Development
Compensation & Rewards
Skills Required
- 5+ years of overall experience in Data Engineering
- 2+ years of hands-on experience in AWS Data Architecture and Cloud Data Platforms
- Proven experience designing and implementing enterprise-scale data solutions
- Design secure, scalable enterprise data lakes, data warehouses, and analytics platforms on AWS
- Build and maintain automated real-time and batch ETL/ELT data pipelines
- Create conceptual, logical, and physical data models
- Monitor, troubleshoot, and optimize AWS resources for performance and cost (FinOps)
- Implement data governance, metadata management, masking, and encryption standards
- Mentor junior data engineers and collaborate with Data Scientists, Product, and DevOps teams
- Advanced proficiency in Python
- Advanced proficiency in Scala
- Advanced proficiency in Java
- Expertise in Apache Spark
- Experience with Hadoop
- Experience with Flink
- Deep knowledge of relational (SQL) and NoSQL databases (e.g., Amazon DynamoDB)
- Experience with AWS Lake Formation
- Experience with Terraform
- Experience with AWS CloudFormation
- Version control using Git
- Deployment automation using Jenkins, GitHub Actions, or AWS CodePipeline
- Active AWS Certified Data Engineer
- AWS Certified Solutions Architect
- Familiarity with Databricks
- Familiarity with Snowflake
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
