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.