Senior Data Engineer

Accord Innovations; Kuala Lumpur; On-site; MYR 120,000 - 180,000; Full time

Job summary

Accord Innovations in Kuala Lumpur, Malaysia is seeking a Senior Data Engineer to design, develop, and maintain scalable data platforms supporting enterprise analytics, reporting, regulatory requirements, and business decisions. The role focuses on AWS cloud technologies, data lake and data warehouse architectures, ETL/ELT, IaC using Terraform, data governance, and DR.

Build reliable pipelines, implement Iceberg datasets, and ensure quality, security, and high availability.

Qualifications

• Bachelor's degree in a relevant field or equivalent experience.
• Minimum 3+ years of experience in Data Engineering, Data Warehousing, Data Platform Engineering, or related roles.
• Strong hands-on experience with SQL, Python, PySpark, and Terraform.
• Proficient in AWS services including Glue, Redshift, S3, RDS, SNS, Step Functions, CloudWatch, IAM, EventBridge, DataZone.
• Experience designing and supporting enterprise Data Lake and Data Warehouse solutions.
• Familiarity with Iceberg tables and large-scale data processing platforms.
• Knowledge of ETL/ELT methodologies, data modeling, and data integration techniques.

Responsibilities

• Design, develop, and maintain scalable, reliable, and secure data pipelines for analytics and reporting.
• Build and optimize ETL/ELT processes to ingest, transform, and load data 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 for enterprise workloads.
• Ensure data quality, accuracy, and timeliness from source systems to Data Lake.
• Monitor, troubleshoot, and resolve data ingestion issues; perform root cause analysis.
• Collaborate with stakeholders to ensure regulatory and governance requirements are met.

Skills

SQL

Python

PySpark

Terraform

AWS

Data Lake/Warehouse design

ETL/ELT

Data Governance

Iceberg

DevOps

Education

Bachelor's Degree in Computer Science, Information Technology, Data Engineering, Engineering, Information Systems, or related discipline

Tools

AWS Glue

Amazon Redshift

Amazon S3

Amazon RDS

Amazon SNS

AWS Step Functions

Amazon CloudWatch

AWS IAM

Amazon EventBridge

AWS DataZone

Apache Iceberg

Job description

We are hiring for one of our client in Kuala Lumpur, Malaysia, 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

• 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.
• 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 Solutions Architect
• AWS Certified Developer
• 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.