Sr AWS Data Architect (AWS Data Platform)

Ccube

$125K — $150K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years in data engineering, with 3+ years in cloud data architecture
  • Strong expertise in AWS core services such as S3, Redshift, and Glue
  • Advanced proficiency in programming languages like Python, Scala, or Java
  • Deep knowledge of SQL and NoSQL database technologies
  • Experience with Infrastructure as Code (IaC) tools such as Terraform or AWS CloudFormation
  • Familiarity with modern data stack tools like Databricks and Snowflake

Responsibilities

  • Design secure and scalable enterprise data lakes and analytics platforms on AWS
  • Build and maintain automated ETL/ELT data pipelines using distributed processing
  • Create data models to support reporting and machine learning initiatives
  • Monitor and optimize AWS resources for performance and cost-efficiency
  • Implement data governance and security standards in compliance with regulations
  • Mentor junior data engineers and collaborate with cross-functional teams

Benefits

  • Hybrid work model (3 days a week in office)
  • Opportunities for professional development and mentorship
  • Collaborative and innovative work environment
  • Exposure to cutting-edge data technologies and cloud solutions
Full Job Description
Sr Data Architect (AWS Data Platform)
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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