Python / GCP Data Engineer from only Eastern Europe

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.