Designing, developing, and maintaining data pipelines and ETLs that ensure reliability, scalability, and discoverability
Building and maintaining ETL/orchestration workflows and troubleshooting data pipeline issues
Operating within cloud environments (Azure and/or AWS), managing and integrating cloud services effectively
Developing infrastructure-as-code scripts for consistent, scalable data environments
Supporting data governance and quality frameworks to maintain data integrity and compliance
Implementing automated testing (unit, integration, end-to-end, contract) to maintain data reliability.
Providing technical guidance on data integration, transformation, and analytics, and building dashboards for product teams
Collaborating with cross-functional teams to design and deliver solutions that meet both business and technical needs.

3+ years of experience in data engineering, database development, and cloud-based data solutions
A degree in a technical field (e.g., Computer Science, Engineering) or equivalent professional experience
Strong proficiency in SQL and database technologies (e.g., SQL Server, PostgreSQL)
Proficiency in Python and/or PySpark, with the ability to write clean, efficient, and reusable code for data processing and transformation.
Hands-on experience with ETL/orchestration tools and frameworks (e.g., Azure Data Factory, Azure Databricks, Apache Airflow, or equivalent).
Cloud experience with major providers (Azure and/or AWS)
Experience with data modeling, data integration, and data warehousing concepts
Knowledge of infrastructure as code
Knowledge of data governance, quality frameworks, and security best practices
Experience working with large, diverse datasets and building scalable data solutions.

Data Engineer

Key skills