Senior Data Engineer (100% WFH)

Qmulus Solutions; Manila; Remote; PHP 1,200,000 - 2,000,000; Full time

Benefits offered by this job

Remote work setup

Graveyard shift option

Career growth opportunities

Global team collaboration

Job summary

Qmulus Solutions is expanding its offshore operations in the Philippines and seeks a Senior Data Engineer to join our global data organization. You will design, build, and optimize scalable data infrastructure across AWS, Snowflake, and Databricks, collaborating with IT, Security, and business stakeholders.

As a hands-on contributor, you will develop robust data pipelines, implement data quality checks, and support analytics and AI initiatives while ensuring performance, reliability, and cost

Qualifications

• 6+ years of professional experience in data engineering or related field.
• Strong hands-on experience with AWS, Snowflake, and Databricks.
• Advanced SQL, Python, and data modeling skills.
• Experience designing production-grade ETL/ELT pipelines.
• Knowledge of dbt and modern data engineering practices.
• Ability to work independently and collaborate with stakeholders.

Responsibilities

• Design, develop, and maintain scalable data pipelines across AWS, Snowflake, and Databricks.
• Optimize data storage and transformation for performance and cost efficiency.
• Develop SQL and Python data transformations to support analytics and reporting.
• Implement robust data models using dbt and modern practices.
• Build data ingestion and integration with CRM/ERP/systems.
• Implement data quality checks, monitoring, and orchestration.
• Collaborate with BI teams to support enterprise reporting and analytics.
• Support data governance, lineage, RBAC, and PII protection.
• Partner with cross-functional teams to translate business requirements into data solutions.

Skills

SQL

Python

Data Modeling

ETL/ELT

Cloud Data Architecture

Independent worker

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

Snowflake

Databricks

dbt

Airflow

Excel

Job description

Qmulus Solutions is more than just a trusted Virtual Staffing provider headquartered in Victoria, BC—we’re a people-first company redefining how teams connect across borders. With a reputation for excellence and innovation, we’re proud to be expanding our offshore operations in the Philippines, creating exciting opportunities for talented professionals to join a dynamic, global team. As we continue to scale, we’re looking for passionate individuals ready to make an impact and grow with us.

We're looking for an experienced Senior Data Engineer to join our Client's global data organization and serve as a senior technical contributor responsible for designing, building, and optimizing scalable enterprise data infrastructure and analytical data solutions across AWS, Snowflake, and Databricks. You will work at the intersection of data engineering, analytics, and business operations to ensure enterprise data is efficiently ingested, transformed, managed, and made accessible for reporting, analytics, and AI-driven applications.

Operating as a highly experienced individual contributor, you will collaborate with Data Engineering, IT, Security, and cross-functional business stakeholders to develop reliable, high-performance data pipelines, optimize cloud data environments, and deliver trusted data products across the organization.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows across AWS, Snowflake, and Databricks.
• Manage and optimize enterprise data storage, processing, and transformation within cloud-based data platforms, ensuring performance, reliability, and cost efficiency.
• Develop and maintain advanced SQL and Python-based data transformations to support analytical workloads, reporting, and downstream applications.
• Design and implement robust data models using dbt and modern data engineering practices to deliver reliable, reusable, and high-performance data products.
• Build and maintain data ingestion and integration processes connecting enterprise systems, including CRM, ERP, cloud platforms, and product applications.
• Implement automated data quality checks, monitoring, validation, and orchestration to ensure data accuracy, consistency, and availability.
• Optimize Snowflake warehouses, Databricks workloads, and AWS-based data services for efficient processing of large-scale datasets.
• Collaborate with analytics and business intelligence teams to support enterprise reporting, semantic models, and certified data sources.
• Support data governance initiatives, including data lineage, cataloging, Role-Based Access Control (RBAC), and Personally Identifiable Information (PII) protection.
• Partner with cross-functional stakeholders across GTM, Finance, Product, CX, Legal, and People teams to translate complex business requirements into scalable technical data solutions.
• Support data infrastructure and architecture requirements for machine learning, AI, and advanced analytics applications.

Job Specification

• 6+ years of professional experience in data engineering, analytics engineering, or a closely related technical data role.
• Strong hands-on experience working with AWS, Snowflake, and Databricks, including managing, transforming, and optimizing enterprise data within these environments.
• Advanced SQL proficiency, including complex transformations, query optimization, performance tuning, and data modeling.
• Strong Python programming skills for data engineering, scripting, automation, and pipeline development.
• Demonstrated experience designing, developing, and maintaining production‑grade ETL/ELT pipelines and data integration workflows.
• Experience with modern data modeling and transformation frameworks, including dbt.
• Solid understanding of cloud data architecture, data warehousing, and scalable data processing methodologies.
• Experience implementing data quality, monitoring, and operational reliability practices within enterprise data environments.
• Ability to work independently, troubleshoot complex technical challenges, and collaborate effectively with technical and business stakeholders.

Preferred Qualifications:

• Experience with AWS data services such as S3, Glue, Lambda, Redshift, and related data integration technologies.
• Experience with Databricks, Apache Spark, Delta Lake, and distributed data processing.
• Advanced Snowflake experience, including warehouse optimization, data sharing, security, and performance management.
• Familiarity with workflow orchestration tools such as Apache Airflow or similar platforms.
• Experience with CI/CD pipelines, Git-based version control, and infrastructure-as-code practices.
• Experience supporting enterprise BI platforms such as Tableau and developing certified analytical data sources.
• Familiarity with data governance frameworks, data catalogs, lineage tracking, RBAC, and PII masking.
• Experience preparing and managing data for machine learning, AI, and vector database applications.
• Experience integrating data from enterprise CRM, ERP, CSP, and SaaS platforms.

Working Conditions

• Remote, work-from-home setup
• 5-day work week
• A culture of collaboration and mentoring

At Qmulus, we believe success isn’t just about skills—it’s about culture, collaboration, and care. We’re proud to foster:

• A culture-oriented workplace where employees feel valued and supported
• Happy employees, happy clients—we thrive on positive relationships
• Comprehensive employee benefits designed with your wellbeing in mind
• Virtual engagement activities that connect our global teams
• Strong management and employee engagement, ensuring every voice is heard

Keep doing what you’re great at. Choose Qmulus—where your growth and wellbeing matter!

Job Type: Full-time

Application Question(s):

• Are you amenable working in graveyard shift?