AWS Data Architect

Role: AWS Data Architect

Location:
Torrance CA Onsite-4 days a week

Duration:
Long Term

• Architect and implement a scalable data hub solution on AWS using best practices for data ingestion, transformation, storage, and access control.
• Define data models, data lineage, and data quality standards for the Datahub.
• Select appropriate AWS services (S3, Glue, Redshift, Athena, Lambda) based on data volume, access patterns, and performance requirements.
• Come up with a design that accommodates AI/ML applications in the next phase.
• Data Ingestion and Integration:
• Design and build data pipelines to extract, transform, and load data from various sources (databases, APIs, flat files) into the Datahub using AWS Glue, AWS Batch, or custom ETL processes.
• Implement data cleansing and normalization techniques to ensure data quality.
• Manage data ingestion schedules and error handling mechanisms.
• Data Governance and Access Control:
• Establish data access controls and security policies to protect sensitive data within the Datahub using IAM roles and policies.
• Develop data governance frameworks including data quality checks, data lineage tracking, and data retention policies.
• Data Analytics Enablement:
• Create data catalogs and metadata management systems to facilitate data discovery and understanding by business users and data analysts.
• Design and implement data views and dashboards using Power BI to enable data exploration and visualization.
• Create data warehouses and data marts to meet the needs of the business.
• Monitoring and Optimization:
• Monitor data pipeline performance, data quality, and system health to identify and resolve issues proactively.
• Optimize data storage and processing costs by leveraging AWS cost optimization features.
• Data Exchange
• Develop the required governance, security, monitoring and guard rails to enable efficient data exchange between internal application and their external vendors, partners, and SaaS providers.
• Develop intake process, SLAs, and usage rules for internal and external data set producers and consumers.

• AWS Expertise:
  Deep understanding of AWS data services including S3, Glue, Redshift, Athena, Lake Formation, Sep Functions, Cloud Watch and Event Bridge.
• Data Modeling:
  Proficiency in designing dimensional and snowflake data models for data warehousing and data lakes.
• Data Engineering
  
  Skills:
  
  Experience with ETL/ELT processes, data cleansing, data transformation, and data quality checks. Experience with Informatica IICS and ICDQ is a plus.
• Programming
  
  Languages:
  
  Proficiency in Python, SQL, and potentially Pyspark for data processing and manipulation.
• Data Governance:
  Knowledge of data governance best practices including data classification, access control, and data lineage tracking.

• Experience with data lake house architectures and the ability to leverage both structured and unstructured data.
• Familiarity with data visualization tools like Tableau or Power BI.
• Strong communication and collaboration skills to work with stakeholders across business and technical teams.
• AWS certifications related to data analytics and architecture.