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> Djinni
senior

Data Engineer

2k–3k USD
format:Remotetype:Full-time
pythongoogle cloudfastapibigqueryapache icebergsqletldata modelingpartitioningdockerci/cdiamrest-apimicroservices
fhirhl7airflowdbtapache beamapache sparkterraformpostgresqlredisobservability
experience4+ years
domainHealthTech
> full description

Position: 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)

 

Job Overview

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.