AWS Data Architect

Job Title: AWS Data Architect
Experience: 10+ Years
Start Date: Immediate – Next Monday/Tuesday
Job Type: Contract - 12 Months
Location: Remote

Job Description:

We are seeking a highly skilled and experienced AWS Data Architect to design, develop, and manage scalable, secure, and high-performance data solutions on Amazon Web Services (AWS). The ideal candidate will have extensive experience in AWS data services, data lake architecture, ETL/ELT pipelines, big data processing, data modeling, and real-time data integration.

The candidate will work closely with data engineers, data scientists, analysts, and business stakeholders to build reliable data platforms that support business intelligence, analytics, and data-driven decision-making.

Key Responsibilities

1. Data Pipeline Development and Management

• Design, develop, and maintain scalable data pipelines using AWS Glue, Amazon Kinesis, AWS Lambda, and Step Functions.

• Build and optimize ETL/ELT workflows for processing large volumes of structured and unstructured data.

• Implement batch and real-time data ingestion and processing solutions.

• Monitor pipeline performance, reliability, and service-level agreements (SLAs).

2. Data Lake, Storage, and Architecture

• Design and implement AWS data lake and data warehouse solutions using Amazon S3, Redshift, Athena, DynamoDB, and RDS.

• Develop efficient data partitioning, indexing, storage, and retrieval strategies.

• Implement data lifecycle management, archiving, and cost optimization practices.

• Ensure data security, availability, integrity, and scalability across AWS environments.

3. Data Transformation and Big Data Processing

• Develop data transformation solutions using AWS Glue, Amazon EMR, and Athena.

• Apply Apache Spark and other big data frameworks to process large-scale datasets.

• Implement data quality checks, validation rules, and error-handling mechanisms.

• Optimize SQL queries, data models, and processing workflows for performance.

4. Data Integration and Automation

• Integrate data from APIs, relational databases, third-party applications, and other enterprise systems.

• Automate ingestion, transformation, and data export workflows using AWS Lambda and Step Functions.

• Ensure data consistency and reliability across multiple systems and environments.

• Implement CI/CD pipelines and version control practices using Git and AWS CodePipeline.

5. Security, Governance, and Compliance

• Implement data governance, access control, encryption, and security best practices.

• Collaborate with security and compliance teams to meet organizational and regulatory requirements.

• Establish monitoring, logging, and auditing standards for data platforms.

6. Monitoring, Troubleshooting, and Optimization

• Monitor data pipelines using Amazon CloudWatch and AWS X-Ray.

• Troubleshoot pipeline failures, data quality issues, and performance bottlenecks.

• Perform root-cause analysis and implement preventive measures.

• Optimize AWS resource utilization and infrastructure costs.

7. Collaboration and Technical Leadership

• Collaborate with data engineers, data scientists, analysts, and business stakeholders.

• Translate business requirements into scalable data architecture solutions.

• Provide technical guidance, architectural best practices, and mentorship to engineering teams.

Required Qualifications

• 10+ years of experience in data architecture, data engineering, or related roles.

• Strong hands-on experience with AWS data services, including Amazon S3, AWS Glue, Amazon Redshift, Athena, Kinesis, Lambda, and Step Functions.

• Experience designing and implementing AWS-based data lakes and data warehouse architectures.

• Strong understanding of ETL/ELT processes, data modeling, data integration, and data pipeline architecture.

• Hands-on experience with Apache Spark and big data technologies such as Hadoop and Apache Flink.

• Proficiency in Python, Java, or Scala.

• Strong SQL skills, including query optimization and performance tuning.

• Experience with relational and NoSQL databases, including Amazon RDS and DynamoDB.

• Experience with CI/CD, Git, and infrastructure automation tools such as Terraform or AWS CloudFormation.

• Strong understanding of data security, governance, data quality, and compliance.

• Experience with batch and real-time data processing architectures.

• Familiarity with containerization and orchestration technologies such as Amazon ECS and EKS.

• Excellent analytical, problem-solving, communication, and collaboration skills.

Preferred Qualifications

• AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect, or relevant AWS data certifications.

• Experience designing enterprise-scale, cloud-native data platforms.

• Experience with data observability, automated data quality monitoring, and cost optimization.

• Experience implementing Infrastructure as Code (IaC) and automated deployment strategies.

Candidates must be authorized to work in the United States as s.

Availability

Immediate start preferred. Candidates should be available to start next Monday or Tuesday.