AWS Data Architect

As a highly experienced Senior Data Architect, your role will involve leading enterprise data and analytics strategy on AWS. You will design and deliver scalable data platforms, data pipelines, and ML systems. Your responsibility will also include driving multi-cloud data architecture, governance, and providing technical leadership across teams. Key Responsibilities: - Define and lead enterprise data architecture and cloud data strategy with a focus on AWS. - Design scalable data lakes, lakehouse, data warehousing (DWH), streaming, and analytics platforms. - Architect and 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, and lineage frameworks. - Mentor data engineering and data science teams, ensuring adherence to architectural best practices. Qualifications Required: - 10+ years of experience in data architecture and engineering, with at least 5 years on cloud platforms (AWS). - Expertise with AWS data stack including S3, Glue, Redshift, Athena, EMR, Kinesis, and Lake Formation. - Strong data modeling skills in dimensional, Data Vault, and lakehouse approaches. - Proficiency in Python, PySpark, SQL, and distributed systems like Spark and Kafka. - Experience with ML platforms such as SageMaker, MLOps, pipelines, and deployment. - Familiarity with multi-cloud environments (AWS + Azure) including data migration and modernization. In addition to the qualifications, the following certifications are mandatory: - AWS Certified Data Analytics Specialty - AWS Certified Machine Learning Specialty - Azure Data Engineer Associate (DP-203) Nice to Have skills include: - Additional AWS certifications such as SA Pro or DevOps Pro. - Experience with Azure DP-100, Databricks, Terraform, or CloudFormation. - Knowledge of data mesh, data fabric, and governance platforms like Alation or Collibra.,