AWS Data Architect

Role Overview:

We are looking for a highly experienced Senior Data Architect to lead enterprise data and analytics strategy on AWS. This role will design and deliver scalable data platforms, data pipelines, and ML systems, while driving multi-cloud data architecture, governance, and technical leadership across teams.

Key Responsibilities

• Define & lead enterprise data architecture and cloud data strategy (AWS-focused).
• Design scalable data lakes, lakehouse, DWH, streaming & analytics platforms.
• Architect & optimize AWS-based ETL/ELT, ML, and real-time data pipelines.
• Lead multi-cloud (AWS + Azure) and hybrid data integration initiatives.
• Implement data governance, security, quality, metadata & lineage frameworks.
• Mentor data engineering & data science teams; ensure architectural best practices.
• 10+ years in data architecture / engineering, 5+ years on cloud platforms (AWS).

Required Skills:

• Expertise with AWS data stack (S3, Glue, Redshift, Athena, EMR, Kinesis, Lake Formation).
• Strong data modeling (dimensional, Data Vault, lakehouse).
• Hands-on Python, PySpark, SQL & distributed systems (Spark, Kafka).
• ML platform experience (SageMaker, MLOps, pipelines & deployment).
• Multi-cloud experience (AWS + Azure) with data migration & modernization.

Certifications Required:

• AWS Certified Data Analytics Specialty
• AWS Certified Machine Learning Specialty
• Azure Data Engineer Associate (DP-203)

Nice to have

• Additional AWS certifications (SA Pro / DevOps Pro)
• Azure DP-100, Databricks, Terraform / CloudFormation experience
• Experience with data mesh, data fabric, governance platforms (Alation/Collibra)

Skills Required
glue , Data Modeling, Spark, Kafka, S3, Emr, Redshift, Pyspark, Distributed Systems, Sql, MLops, Azure, Kinesis, Python