Data Engineer

Data pipeline development and optimization
· Design, build, and maintain efficient, scalable ETL/ELT pipelines for structured and unstructured data.
· Continuously monitor and optimize pipeline performance for speed and resource utilization.
· Implement modular, reusable Python- based processing scripts and manage job orchestration using Power Automate, Linux cron, or other scheduling frameworks.
Cloud infrastructure and cost management
· Deploy and manage data infrastructure leveraging AWS services (e.g. Lambda, Glue, S3, RDS, Athena).
· Ensure system uptime, data accessibility, and high availability across environments.
· Proactively optimize storage and compute costs through monitoring, automation, and right- sizing of resources.
Automation, CI/CD & DevOps practices
· Maintain a clean, testable codebase with proper version control and documentation.
· Automate deployment workflows using GitLab CI/CD pipelines.
· Introduce best practices for environment provisioning, rollback, and automated testing.
Data quality, security & governance
· Implement robust data validation, logging, and monitoring practices across pipelines.
· Ensure data privacy, integrity, and lifecycle compliance in collaboration with IT security policy.
· Maintain documentation including data dictionaries, flow diagrams, and operational runbooks.
Cross team technical support & enablement
· Provide technical guidance on data ingestion, transformation, and storage patterns.
· Collaborate with IT, software, and business system teams to integrate backend data solutions.
· Ensure that platform components (pipelines, storage, compute) support the broader application and reporting ecosystem.

Required Competencies
· Solid understanding of data pipeline orchestration (e.g., cron, Airflow, Power Automate) and containerization (e.g., Docker)
· Strong programming skills in Python, with experience building modular and reusable components for data workflows
· Familiar with version control, infrastructure documentation, and maintaining data dictionaries or runbooks
· Fluent in CI/CD and automation frameworks, particularly using GitLab pipelines, Power Automate, and scripting on Linux/Windows environments
· Demonstrated ability to collaborate with cross- functional technical teams, supporting data infrastructure integration and maintenance
· Proficient in SQL for data manipulation and performance tuning across relational databases (PostgreSQL, MySQL)
· Hands- on experience with AWS services such as Lambda, Glue, S3, RDS, and Athena, with a focus on cost and performance optimization
· Knowledge of data governance, privacy, and quality control, including validation, monitoring, and alerting mechanisms
Qualification and Experience Required
· Familiarity with data quality, security, and governance best practices
· Proven track record in building and maintaining production- grade ETL/ELT pipelines using Python and SQL
· Minimum 3 years of hands- on experience in a data engineering or backend data infrastructure role
· Professional certification in data engineering, cloud architecture, or AWS (e.g., AWS Certified Data Analytics or Solutions Architect) is an advantage
· Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field
· Experience in a multi- business or regional group environment is a plus
· Experience working with DevOps practices, CI/CD pipelines (e.g., GitLab), and automation tools for deployment and workflow orchestration
· Demonstrated experience managing cloud- based infrastructure, with a strong understanding of cost optimization, monitoring, and scalability (preferably on AWS)

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Cập nhật gần nhất lúc: 2026-01-15 06:50:03