Aws Data Architect

Key Responsibilities

• Data Architecture Design

• 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 AIML 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

Required Skills and Experience

• AWS Expertise Deep understanding of AWS data services including S3 Glue Redshift Athena Lake Formation Sep Functions CloudWatch and EventBridge

• Data Modeling Proficiency in designing dimensional and snowflake data models for data warehousing and data lakes

• Data Engineering Skills Experience with ETLELT 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

• Preferred Qualifications

• Experience with data lakehouse 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

Skills

Mandatory Skills : Apache Airflow, Athena, Aurora, AWS MWAA, QuickSight