Passionate about AWS and Data? Ccube wants you on the team!
We are looking for a highly skilled "Senior AWS Data Platform Architect" to join our growing data and cloud team in Indore. The ideal candidate will be responsible for designing enterprise-scale data architectures, building robust data pipelines, and implementing scalable cloud-native data platforms on AWS.
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.
Sr AWS Data Platform Architect
Location:- Missisauga, ON (Hybrid, 3 Days a Week)
Full Time
Experience: 10+ years in data engineering, with at least 3+ years focusing on cloud data architecture.
About the Role
We are seeking a highly skilled and visionary Sr AWS Data Architect to design, build, and optimize our next-generation data platforms. In this role, you will bridge the gap between high-level architectural strategy and hands-on engineering, transforming raw data into actionable business insights. You will architect scalable data lakes, design robust ETL pipelines, and ensure our cloud infrastructure remains secure, performant, and cost-effective.
Key Responsibilities
- Data Architecture: Design secure, scalable, and future-proof enterprise data lakes, data warehouses, and analytics platforms on AWS.
- Pipeline Engineering: Build and maintain automated, real-time, and batch ETL/ELT data pipelines using distributed processing frameworks.
- Data Modeling: Create conceptual, logical, and physical data models to support reporting, advanced analytics, and machine learning initiatives.
- Cloud Optimization: Monitor, troubleshoot, and optimize AWS resources for maximum performance and cost efficiency (FinOps).
- Governance & Security: Implement data governance, metadata management, masking, and encryption standards in compliance with industry regulations.
- Leadership & Collaboration: Mentor junior data engineers and collaborate closely with Data Scientists, Product Managers, and DevOps teams to align data solutions with business goals.
Must-Have Technical Skills
AWS Core Services: Amazon S3, Amazon Redshift, AWS Glue, Amazon EMR, Amazon Kinesis, and AWS IAM.
Programming Languages: Advanced proficiency in Python, Scala, or Java.
Data Processing: Expertise in distributed computing frameworks like Apache Spark, Hadoop, or Flink.
Database Technologies: Deep knowledge of both relational (SQL) and NoSQL databases (e.g., Amazon DynamoDB).
Data governance: AWS Lake formation
Infrastructure as Code (IaC): Experience with Terraform or AWS CloudFormation.
DataOps/CI/CD: Version control (Git) and deployment automation using tools like Jenkins, GitHub Actions, or AWS Code pipeline.
Preferred Qualifications
Certifications: AWS Certified Solutions Architect.
Modern Data Stack: Familiarity with tools like Databricks, Snowflake.
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