Sr AWS Data Architect; AWS Data Platform

Passionate about AWS and Data? Ccube wants you on the team!

We are looking for a highly skilled "Senior AWS Data 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.

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.

We are seeking a highly skilled and visionary SrAWS 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.

• 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 (Fin Ops).
• 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 Dev Ops teams to align data solutions with business goals.

AWS Core Services:Amazon S3, Amazon Redshift, AWS Glue, Amazon EMR, Amazon Kinesis, and AWS IAM.

Programming Language
s:
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 No

SQL databases (e.g., Amazon DynamoDB).

Data governance:AWS Lake formation

Infrastructure as Code (IaC):Experience with Terraform or AWS Cloud Formation.

Data Ops/CI/CD:Version control (Git) and deployment automation using tools like Jenkins, Git Hub Actions, or AWS Code pipeline.

Certifications:AWS Certified Solutions Architect.

Modern Data Stack:Familiarity with tools like Databricks, Snowflake.