Compensation: $30k – $40k • No equity
Position: Mid or Senior Python / GCP Data Engineer
Location: Remote
Employment Type: Full-Time
Salary: $2,000–$3,000 USD per month (depending on experience)
Working Hours: Must be available during U.S. business hours (Eastern Time Zone)
Experience Level: Mid-Level to Senior (4+ years preferred)
We are looking for an experienced Python / GCP Data Engineer to design, develop, and maintain scalable data pipelines, backend APIs, and cloud-based data processing systems.
The ideal candidate has strong experience with Google Cloud Platform (GCP), Python, FastAPI, BigQuery, Apache Iceberg, and DuckDB, along with a solid understanding of modern data engineering architectures.
Experience in the healthcare industry is highly preferred, particularly working with healthcare datasets, FHIR, HL7, or HIPAA-compliant systems.
** Key Responsibilities**
- Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Python and GCP.
- Develop high-performance RESTful APIs and microservices using FastAPI.
- Build and optimize analytical data solutions using BigQuery, Apache Iceberg, and DuckDB.
- Integrate data from multiple sources, including REST APIs, databases, cloud storage, and third-party systems.
- Design and maintain data lake and lakehouse architectures.
- Work with GCP services such as Cloud Run, Cloud Functions, Cloud Storage, Pub/Sub, Dataflow, Dataproc, and Cloud Composer.
- Optimize SQL queries, data processing performance, and cloud infrastructure costs.
- Implement data validation, quality checks, monitoring, and error handling.
- Develop automated testing and CI/CD pipelines for backend services and data workflows.
- Collaborate with engineering and product teams to deliver reliable, production-ready solutions.
- Implement secure data access, authentication, and authorization following cloud security best practices.
** Required Qualifications**
- 4+ years of professional experience in Python backend development or data engineering.
- Strong hands-on experience with Google Cloud Platform (GCP).
- Advanced Python programming skills, including asynchronous programming and data processing.
- Production experience building APIs using FastAPI.
- Strong SQL skills and experience with Google BigQuery.
- Experience with Apache Iceberg, DuckDB, or similar modern analytical data technologies.
- Experience building ETL/ELT pipelines and handling large datasets.
- Familiarity with data modeling, partitioning, indexing, and query optimization.
- Experience with Docker, Git, and CI/CD pipelines.
- Understanding of cloud IAM, service accounts, authentication, and security.
- Strong debugging, troubleshooting, and problem-solving skills.
- Good English communication skills.
** Preferred Qualifications**
- Previous experience in the U.S. healthcare industry.
- Knowledge of healthcare data standards such as FHIR, HL7, and EHR/EMR integrations.
- Understanding of HIPAA compliance and secure handling of PHI/PII.
- Experience with GCP Healthcare API and FHIR data processing.
- Experience with Apache Airflow, dbt, Apache Beam, or PySpark.
- Familiarity with Terraform and Infrastructure as Code.
- Experience with PostgreSQL, Redis, or other database technologies.
- Knowledge of data governance, observability, and performance monitoring.
** Working Hours & Availability**
U.S. time zone availability is a strict requirement for this position.
- Must be available during U.S. Eastern Time (ET) business hours.
- Full-time commitment of approximately 40 hours per week.
- Must be able to attend daily standups, technical discussions, and team meetings.
- Strong communication skills and responsiveness during working hours are essential.
- Candidates unable to maintain consistent U.S. time zone availability will not be considered.
** Compensation**
$2,000–$3,000 USD per month, based on technical expertise, relevant experience, and interview performance.
This is a fully remote, long-term opportunity to work on cloud-native data engineering and backend systems, with a focus on scalable, secure, and reliable solutions.