Jobs at Aws in Singapore

The Data Lead AWS Solution Consultant will play a key role in designing, building, and implementing advanced data solutions on AWS. This position requires a deep understanding of data engineering, cloud architecture, and analytics to deliver scalable and high-performing solutions. The Data Lead will collaborate with cross-functional teams to address complex business challenges, define best practices, and drive innovation in data analytics and cloud services.

Key Responsibilities

Data Architecture and Solution Design

• Design and implement end-to-end data architectures on AWS, including data pipelines, data lakes, and warehouses.
• Translate business requirements into scalable and sustainable AWS-based data solutions.
• Develop and maintain reusable cloud data patterns, ensuring alignment with organizational objectives.
• Define strategies for migrating data applications and workloads to AWS, including cost and performance optimization.
• Collaborate with stakeholders to identify and implement the best architectural patterns for data analytics needs.

Data Engineering and Operations

• Lead the development of data ingestion, transformation, and storage pipelines using AWS services such as Glue, Redshift, and S3.
• Implement automation s and templates using tools like Terraform and CloudFormation for cloud resource provisioning.
• Ensure data governance, security, and compliance in all cloud-based data solutions.
• Provide guidance and expertise in resolving integration and operational challenges for AWS PaaS and IaaS services.
• Optimize data workflows and analytics solutions for performance and cost-effectiveness.

Collaboration and Documentation

• Work closely with DevOps, engineering, and analytics teams to ensure seamless integration of cloud solutions.
• Develop comprehensive documentation, including playbooks, reference architectures, and operational guides.
• Mentor and guide team members on AWS best practices and emerging technologies.
• Engage with vendors and partners to assess and implement scalable AWS-based tools and solutions.

Analytics and Insights

• Build and optimize data models, including star and snowflake schemas, for analytics and reporting.
• Incorporate advanced analytics techniques such as machine learning, data visualization, and real-time processing.
• Utilize AWS analytics tools (e.g., QuickSight, Redshift) and third-party tools (e.g., Power BI, Tableau) for interactive reporting and dashboards.

Requirements

Education and Experience

• Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field.
• At least 8 years of experience in data engineering, cloud architecture, and advanced analytics, with a focus on AWS.

Technical Expertise

• AWS Services: Proficiency in AWS Glue, Redshift, Athena, Lambda, S3, EMR, and other AWS data services.
• Infrastructure as Code: Experience with Terraform and CloudFormation for AWS resource provisioning.
• Databases: Expertise in relational and non-relational databases, including Aurora, DynamoDB, and Databricks.
• Programming: Strong skills in SQL, Python, and PySpark for data processing and transformation.
• Data Tools: Experience with ETL tools, data quality frameworks, and data orchestration tools like Apache Airflow.
• Visualization: Proficiency in tools such as AWS QuickSight, Power BI, and Tableau.
• Analytics Models: Familiarity with predictive analytics, machine learning frameworks, and real-time data processing.

AWS Certifications (Preferred)

• AWS Certified Solutions Architect Professional.
• AWS Certified Data Analytics Specialty.
• AWS Certified DevOps Engineer Professional.