We are looking for a skilled Data Architect to join our team. This role involves designing and implementing data solutions on the cloud, including data lakes, warehouses, and pipelines. You’ll collaborate with teams to ensure data is accessible, optimized, and secure for analytics and business intelligence.

REQUIRED SKILLS & EXPERIENCE:

• Extensive experience with AWS services like Redshift, S3, Glue, RDS, and DynamoDB for building data architectures.
• Strong background in designing and automating ETL/ELT pipelines using AWS Glue, Spark, and Python.
• Expertise in data modeling, structuring relational and NoSQL data for optimal performance.
• Familiarity with data governance, encryption, IAM, and regulatory compliance (e.g., GDPR, SOC 2).
• Experience with frameworks like Hadoop, Spark, or Kafka for processing large datasets.
• Proficiency in Python, SQL, and Java for developing custom data workflows and querying large datasets.
• Knowledge of infrastructure management tools such as CloudFormation, Terraform, or AWS CDK.
• Ability to work across teams (data engineers, analysts, business stakeholders) to deliver data solutions that meet business needs.

PREFERRED QUALIFICATIONS:

• AWS Certified Solutions Architect – Associate, AWS Certified Big Data – Specialty, or similar certifications.
• Experience with AWS Kinesis, Kafka, or other real-time data streaming technologies.
• Familiarity with tools like Apache Atlas or AWS Glue Data Catalog.
• Experience integrating data systems with machine learning workflows.
• Experience with services like Amazon EMR, Redshift Spectrum, and AWS Data Pipeline.
  If you’re an experienced Data Architect with a strong background in AWS and data solutions, we’d love to hear from you!

• Architect scalable, secure cloud-based data systems using AWS services like Redshift, S3, Glue, and DynamoDB to support analytics and machine learning.
• Develop and manage ETL/ELT workflows, transforming and processing data using AWS Glue, Apache Spark, and custom Python solutions.
• Create and maintain relational and NoSQL data models to ensure efficient querying, storage, and reporting.
• Integrate and consolidate data from diverse sources to ensure accuracy and consistency for analytics.
• Implement data governance and security practices, including encryption, IAM roles, and compliance with GDPR and SOC 2.
• Continuously optimize data systems for performance, cost efficiency, and scalability, ensuring high availability and reliability.
• Partner with data engineers, data scientists, and business analysts to design solutions that meet business needs and enable data-driven decisions.
• Maintain documentation on architecture, workflows, and best practices to ensure consistency and operational continuity.