Data Engineer
Summary
Designs resilient, scalable data pipelines and products using Azure, SQL, Spark, and CI/CD to transform and deliver data for analytics and architecture.
Hybrid - Taguig 5-10 Yrs Exp Bachelor Full-time
Job Description
This position designs data products and data pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost effective. Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design.
Government Mandated Benefits
Insurance Health & Wellness
HMO
Professional Development
Job Training, Professional Development
Responsibilities include, but are not limited to, the following:
- Utilize Azure data storage accounts for organizing and maintaining data pipeline outputs (e.g., Azure Data Lake Storage Gen 2 & Azure Blob storage).
- Collaborate with data scientists, data analysts, data architects and other stakeholders to understand data requirements and deliver high-quality data solutions.
- Optimize data pipelines in the Azure environment for performance, scalability, and reliability.
- Ensure data quality and integrity through data validation techniques and frameworks.
- Develop and maintain documentation for data processes, configurations, and best practices.
- Monitor and troubleshoot data pipeline issues to ensure timely resolution.
- Stay current with industry trends and emerging technologies to ensure our data solutions remain cutting‑edge.
- Manage the CI/CD process for deploying and maintaining data solutions.
Required Qualifications:
- Bachelor’s degree in computer science, engineering, or a related field (or equivalent experience) and ability to demonstrate high proficiency in programming fundamentals.
- Proven experience (7+ years) as a Data Engineer or similar role dealing with data and ETL processes.
- Experience utilizing SQL DML to query modern RDBMS efficiently (e.g., SQL Server, PostgreSQL).
- Strong understanding of software engineering principles and how they apply to data engineering (e.g., CI/CD, version control, testing).
- Experience with big data technologies (e.g., Spark).
- Strong problem‑solving skills and attention to detail.
- Excellent communication and collaboration skills.
Preferred Qualifications:
- Learning agility
- Technical leadership
- Consulting and managing business needs
- Strong experience in Python (preferred but other languages such as Scala, Java, C#, etc. are accepted).
- Experience building spark applications utilizing PySpark.
- Experience with file formats such as Parquet, Delta, Avro.
- Experience efficiently querying API endpoints as a data source.
- Understanding of the Azure environment and related services such as subscriptions, resource groups, etc.
- Understanding of Git workflows in software development.
- Using Azure DevOps pipeline and repositories to deploy and maintain solutions.
- Understanding of Ansible and how to use it in Azure DevOps pipelines.