Data Engineer

Job Requirements
At Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster
We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.
Job Summary
We are looking for an experienced Data Engineer with strong expertise in Python, SQL,
ETL/ELT development, and cloud-based data platforms. The ideal candidate will be
responsible for designing, developing, and maintaining scalable data pipelines, data
warehouses, and analytics-ready datasets that support reporting, business intelligence,
and data-driven decision-making.
The role requires hands-on experience working with large datasets, modern data
engineering frameworks, cloud technologies, and data orchestration tools while
collaborating closely with Data Analysts, Power BI Developers, Product Teams, and
Business Stakeholders.
Key Responsibilities
Data Engineering & Development
Design, develop, and maintain scalable data pipelines using Python and SQL.
Build robust ETL/ELT frameworks for structured and unstructured data processing.
Develop data ingestion solutions from APIs, databases, cloud storage, and external
file sources.
Perform data cleansing, transformation, enrichment, validation, and quality
assurance activities.
Design reusable and maintainable data processing components.
Cloud & Big Data Platforms
Develop and support cloud-native data solutions on AWS and/or Azure.
Build and optimize data workflows using services such as AWS Glue, EMR, Lambda,
S3, RDS or Azure Data Factory, Databricks, Synapse, and ADLS.
Work with large-scale datasets and distributed data processing frameworks.
Data Warehouse & Analytics
Design and maintain data models, data marts, and analytical datasets.
Support enterprise reporting and self-service analytics initiatives.
Optimize database performance and query execution.
Collaborate with Power BI teams on semantic models and reporting datasets.
Data Quality & Operations
Implement data validation frameworks and quality controls.
Develop monitoring, alerting, logging, and operational support processes.
Troubleshoot production data pipeline failures and performance issues.
Support ongoing maintenance and improvements of enterprise data platforms.
Engineering Excellence
Follow coding standards, peer reviews, and software engineering best practices.
Implement CI/CD pipelines for data engineering workloads.
Maintain source control repositories using Git.
Create technical documentation and knowledge-sharing materials.
We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.
Work Experience
Programming
Python (Advanced)
SQL (Advanced)
Linux/Unix Shell Scripting
Data Engineering
ETL/ELT Development
Data Pipeline Development
Data Ingestion Frameworks
Data Transformation
Data Validation
Data Quality Management
Big Data & Processing
Apache Spark
PySpark
Workflow Orchestration
Apache Airflow
Workflow Scheduling Tools
Databases & Warehousing
PostgreSQL
SQL Server
Snowflake
Amazon Redshift
Data Warehousing Concepts
Data Modeling
DevOps & Version Control
Git
CI/CD Fundamentals
Integration
REST API Integration

Work arrangement
No