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.