Sr AWS Data Architect

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.

Sr AWS Data Architect
Location:- Indore, MP (Hybrid)
Full Time

Experience: 10+ years in data engineering, with at least 4+ 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.