Saksoft
AWS Data Architect
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an "AWS Data Architect" with a contract length of "unknown" and a pay rate of "unknown." Candidates should have 11-15 years of experience, strong AWS expertise, data modeling skills, and proficiency in Python and SQL. AWS certifications preferred.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
March 7, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
Torrance, CA
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🧠 - Skills detailed
#IICS (Informatica Intelligent Cloud Services) #Data Cleansing #S3 (Amazon Simple Storage Service) #Normalization #Scala #Tableau #Data Quality #Lambda (AWS Lambda) #Security #Data Ingestion #ML (Machine Learning) #Data Processing #"ETL (Extract #Transform #Load)" #PySpark #Data Modeling #Metadata #Monitoring #Data Management #IAM (Identity and Access Management) #AWS (Amazon Web Services) #Data Architecture #BI (Business Intelligence) #Data Access #Spark (Apache Spark) #SQL (Structured Query Language) #Data Lake #AWS Glue #Athena #Data Catalog #GCP (Google Cloud Platform) #Informatica #Data Lakehouse #Batch #Data Warehouse #Databases #Python #Storage #Microsoft Power BI #SaaS (Software as a Service) #Data Pipeline #Data Storage #Redshift #MDM (Master Data Management) #Visualization #Cloud #Data Lineage #Classification #Programming #Snowflake #Data Governance #AI (Artificial Intelligence) #Data Engineering #Data Mart #Data Analysis #Data Exploration
Role description
Description:
Seeking an Associate Principal with 11~15 years of experience to architect and lead AWS data architecture solutions leveraging AWS services.
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 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
Required Skills and Experience:
· AWS Expertise: Deep understanding of AWS data services including S3, Glue, Redshift, Athena, Lake Formation, Sep Functions, CloudWatch 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.
Preferred Qualifications:
· 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.
Skills:
Mandatory Skills : Data Architecture, Data Lakehouse Architecture, Dimensional Data Modeling, GCP Data Architecture, MDM Conceptual
Description:
Seeking an Associate Principal with 11~15 years of experience to architect and lead AWS data architecture solutions leveraging AWS services.
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 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
Required Skills and Experience:
· AWS Expertise: Deep understanding of AWS data services including S3, Glue, Redshift, Athena, Lake Formation, Sep Functions, CloudWatch 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.
Preferred Qualifications:
· 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.
Skills:
Mandatory Skills : Data Architecture, Data Lakehouse Architecture, Dimensional Data Modeling, GCP Data Architecture, MDM Conceptual
