Job Purpose
The data engineer supports data ingestion, transformation, and reconciliation workflows. This role is ideal for someone with strong SQL capabilities, hands-on Python experience, and exposure to modern data tooling such as DBT and Airflow. You will work under the guidance of a lead engineer and gain experience across endtoend data engineering tasks.
Desired Skills and experience
Essential skills
- Strong proficiency in SQL (Snowflake experience preferred).
- Hands-on experience with Python for data processing and automation.
- Familiarity with dbt for modeling and transformations.
- Exposure to workflow orchestration tools such as Airflow.
- Experience handling or integrating with Excel-based data sources.
- Experience working with structured file-based data sources
- Understanding of basic data modelling principles
- Azure Data Factory or Power Automate experience
Good to have:
- Prior experience modernizing Excelbased or macro-driven business processes.
- Experience delivering data transformation projects involving SQL, cloud warehouses, and orchestration tools.
- Power BI or reporting exposure
Key Responsibilities
- Build and maintain data ingestion pipelines from Excelbased data sources.
- Develop SQL queries and dbt models to support data transformation and analytics requirements.
- Assist in performing reconciliation, validation, and testing of transformed datasets.
- Work closely with and take directions from the lead resource, ensuring consistent and high-quality delivery.
- Troubleshoot issues in data pipelines and contribute to continuous process improvements.
Behavioral Competencies
- Good communication (verbal and written)
- Experience in managing client stakeholders
- Ability to learn quickly and adapt to evolving project needs.
- Detail-oriented with a focus on accuracy in data work.
