全职 Senior Data Engineer 工作, 薪水, R Systems Federal Territory 公司招聘中 - Ricebowl

Job Summary

We are seeking a highly skilled and experienced Senior Data Engineer to join our Data & Analytics team within the Insurance domain. The successful candidate will be responsible for designing, developing, and maintaining scalable, secure, and high-performing data platforms that support enterprise reporting, analytics, regulatory requirements, and business decision-making.

This role requires strong expertise in AWS cloud technologies, data lake and data warehouse architectures, ETL/ELT development, Infrastructure as Code (IaC), data governance, disaster recovery, and modern AI-enabled software development practices. The ideal candidate will be passionate about delivering reliable data solutions, automating processes, enforcing data quality standards, and driving innovation through emerging technologies.

Key Responsibilities

Data Engineering & Data Platform Development

• Design, develop, and maintain scalable, reliable, and secure data pipelines to support enterprise analytics and reporting initiatives.
• Build and optimize ETL/ELT processes to ingest, transform, and deliver data from various source systems into Data Lake and Data Warehouse environments.
• Design, implement, and maintain cloud-native data solutions on AWS.
• Develop scalable batch and near real-time data processing solutions.
• Develop and maintain Apache Iceberg datasets to support enterprise analytical workloads.
• Ensure data from source systems is successfully loaded into the enterprise Data Lake daily with accuracy, completeness, and timeliness.
• Monitor and troubleshoot data ingestion processes and resolve data-related issues proactively.
• Conduct root cause analysis and implement sustainable solutions for recurring incidents.
• Optimize data processing performance, scalability, and operational efficiency.
• Support enterprise reporting, analytics, and regulatory data requirements.

AWS Cloud Platform & Infrastructure

• Design, build, and support AWS-based data platforms using:
• AWS Glue
• Amazon Redshift
• Amazon S3
• Amazon RDS
• Amazon SNS
• AWS Step Functions
• Amazon CloudWatch
• AWS IAM
• Amazon EventBridge
• AWS DataZone
• Develop and maintain Infrastructure as Code (IaC) solutions using Terraform.
• Automate environment provisioning, deployment, and operational processes.
• Implement monitoring, alerting, and operational support frameworks to ensure platform stability and high availability.
• Optimize cloud infrastructure for performance, security, reliability, and cost efficiency.
• Support and enhance CI/CD deployment pipelines and DevOps practices.

Disaster Recovery & Business Continuity

• Participate in Disaster Recovery (DR) planning, validation, and execution activities for critical data platforms and services.
• Perform Disaster Recovery (DR) drills, failover, failback, and recovery procedures within established Recovery Time Objective (RTO) and Recovery Point Objective (RPO) requirements.
• Ensure data pipelines, Data Lake, and Data Warehouse platforms can be recovered and restored during disaster scenarios.
• Maintain and regularly update Disaster Recovery documentation, runbooks, and recovery procedures.
• Collaborate with infrastructure, security, and application teams to ensure business continuity readiness.

Data Governance & Quality Management

• Establish and maintain data quality validation, reconciliation, and monitoring controls.
• Ensure data accuracy, consistency, completeness, and reliability across the data platform.
• Support enterprise data governance initiatives through AWS DataZone, including metadata management, data ownership, and data discoverability.
• Collaborate with stakeholders to define and implement data standards, governance policies, and best practices.
• Ensure compliance with enterprise security, privacy, regulatory, and audit requirements.

Stakeholder Collaboration

• Collaborate closely with Business Analysts, Data Analysts, BI Developers, Architects, Product Owners, and business stakeholders to understand and deliver data requirements.
• Translate business requirements into scalable technical designs and data models.
• Provide technical leadership and guidance on data engineering best practices.
• Partner with cross-functional teams to continuously improve data platform capabilities.

Documentation & Knowledge Transfer

• Create and maintain comprehensive technical documentation, including:
• Solution Design Documents
• Technical Specifications
• Data Flow Diagrams
• Runbooks
• Support Guides
• Operational Procedures
• Disaster Recovery Procedures
• Conduct Knowledge Transfer (KT) sessions to ensure team members understand implemented solutions, processes, and support procedures.
• Promote knowledge sharing, engineering standards, and best practices across the team.
• Mentor junior engineers and support team capability development.

Required Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Data Engineering, Engineering, Information Systems, or a related discipline.
• Minimum 3+ years of experience in Data Engineering, Data Warehousing, Data Platform Engineering, or related roles.
• Strong hands-on experience in:
• SQL
• Python
• PySpark
• Terraform
• Strong experience with AWS services including:
• AWS Glue
• Amazon Redshift
• Amazon S3
• Amazon RDS
• Amazon SNS
• AWS Step Functions
• Amazon CloudWatch
• AWS IAM
• Amazon EventBridge
• AWS DataZone
• Experience designing and supporting enterprise Data Lake and Data Warehouse solutions.
• Experience working with Apache Iceberg tables and large-scale data processing platforms.
• Strong understanding of ETL/ELT methodologies, data modeling, and data integration techniques.
• Experience implementing Infrastructure as Code (IaC) using Terraform.
• Strong understanding of cloud security, IAM permissions, and access control principles.
• Experience planning, executing, and supporting Disaster Recovery (DR) activities, including failover testing, recovery validation, and business continuity processes.
• Knowledge of Agentic AI, Generative AI, and AI-assisted software development practices.
• Experience utilizing AI-powered coding assistants and modern AI development workflows to improve engineering productivity, accelerate delivery, and enhance code quality.
• Strong analytical, problem-solving, troubleshooting, and communication skills.
• Ability to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications

• AWS Certifications, such as:
• AWS Certified Data Engineer
• AWS Certified Solutions Architect
• AWS Certified Developer
• AWS Certified Cloud Practitioner
• Experience with Power BI.
• Knowledge of SAP BusinessObjects (SAP BO).
• Experience implementing AWS DataZone and enterprise data governance frameworks.
• Experience with Data Lakehouse architecture.
• Familiarity with DevOps, CI/CD, and cloud automation practices.
• Experience within the Insurance or Financial Services industry.

Key Competencies

• Data Engineering Excellence
• AWS Cloud Technologies
• Data Lake & Data Warehouse Architecture
• ETL/ELT Development
• Apache Iceberg
• Infrastructure as Code (Terraform)
• AWS DataZone
• Data Governance & Metadata Management
• Disaster Recovery & Business Continuity
• AI-Enabled Data Engineering
• Agentic AI & Generative AI
• Cloud Security & IAM
• Data Quality Management
• Technical Documentation
• Knowledge Transfer & Mentoring
• Stakeholder Management
• Problem Solving & Critical Thinking
• Continuous Improvement & Innovation

Technical Environment

Cloud Platform

• AWS

AWS Services

• AWS Glue
• Amazon Redshift
• Amazon S3
• Amazon RDS
• Amazon SNS
• AWS Step Functions
• Amazon CloudWatch
• AWS IAM
• Amazon EventBridge
• AWS DataZone

Programming & Development

• SQL
• Python
• PySpark
• Terraform
• Git

Data Technologies

• Apache Iceberg
• Data Lake
• Data Warehouse
• ETL/ELT Frameworks
• Data Governance

Analytics & Reporting

• Power BI
• SAP BusinessObjects (SAP BO)

Emerging Technologies

• Agentic AI
• Generative AI
• AI-Assisted Software Development

Nice-to-Have Technologies

• Data Lakehouse Architecture
• Cloud Automation
• CI/CD Pipelines