Data Engineer

About the Role:

We are looking for a Data Engineer who can take ownership of building and managing end-to-end data pipelines across our systems. This role blends data engineering, cloud infrastructure, and API development to power our analytics and data products.

You will be responsible for:

• Building automated data pipelines to extract data from sources like Google Drive and external APIs.
• Writing scalable ETL/ELT processes using Python and DBT for data transformation and modeling.
• Developing API services for both ingesting and consuming data from external partners.
• Managing cloud data infrastructure on Google Cloud (GCS, BigQuery).

Responsibilities:

• Design, build, and maintain data pipelines for ingestion from Google Drive and other external sources into GCP.
• Write DBT models to transform data into analytics-ready datasets in BigQuery.
• Develop Python-based APIs (FastAPI/Flask) for data ingestion and consumption.
• Work with cloud infrastructure (GCP) to manage storage, compute, and orchestration.
• Automate workflows using Airflow/Cloud Composer.
• Optimize data pipeline performance, error handling, and logging.

Tech Stack:

• Google Cloud Platform (BigQuery, Cloud Storage, Cloud Functions, Pub/Sub)
• Python (Pandas, PySpark, API Frameworks like FastAPI/Flask)
• DBT for data modeling
• Airflow (or similar orchestration)
• Google Drive API, REST APIs
• Git for version control

Ideal Profile:

• 3+ years of experience in Data Engineering.
• Strong Python programming skills.
• Hands-on experience with GCP (BigQuery, GCS).
• Experience in building APIs (FastAPI preferred).
• Solid understanding of SQL and DBT.
• Experience in working with external data integrations.

Strong problem-solving skills and ability to work independently.