Middle Data Engineer| Azure Data Factory | Healthcare |Remote | Full-Time (вакансія неактивна)

🌍 About the Project & Client

GreenM is a team of experts in Data Engineering and Software Development, dedicated to helping healthcare organizations efficiently manage data and digital solutions. We specialize in building scalable data platforms, AI development, optimizing business processes, and developing software products that enhance operational efficiency and drive business growth for healthcare companies in the United States and the United Kingdom.

We are expanding our team to support a leading technology company in the healthcare sector that is scaling its Data Engineering capabilities.

The client has strong expertise in data infrastructure and analytics but requires additional specialists to accelerate project execution.

Project Overview: The project focuses on building a robust data analytics and infrastructure hub for lactation consultations under the healthcare domain.

The key objective is to enhance the patient portal, build a scalable Data Warehouse, and transition to a microservices architecture. This is a long-term collaboration with plans for further team expansion in 2025 and beyond.

🎯 Role: Middle Data Engineer

As a Data Engineer, you will work on designing, developing, and optimizing data pipelines for healthcare analytics and reporting. The role requires expertise in data pipeline/workflow tools such as Airbyte and Dagster, cloud expertise in Azure, and expertise in Data Warehouse design, and the ability to work with structured & semi-structured data sources.

🔑 Key Responsibilities:

✅ Data Engineering & ETL Development:

Develop and maintain ETL pipelines in Azure Cloud.

Implement and troubleshoot data pipelines/workflows using Airflow, Airbyte and Dagster tools.

Work on API-based data integrations and third-party connectors.

Support performance monitoring and troubleshooting of data pipelines.

✅ Database Management:

Work on data modeling and schema design

Write and optimize SQL queries for data extraction, transformation, and loading.

Work on database performance tuning and indexing strategies.

✅ Collaboration & Documentation:

Collaborate with Engineers, Business Analysts, and Product Owners to implement data solutions.

Contribute to technical documentation for pipelines, database structures, and integrations.

Participate in code reviews and team discussions to improve best practices.

✅ Reporting and Visualization:

Work with Power BI and D3.

✅ Security & Data Governance:

Follow data governance and security policies.

Ensure compliance with HIPAA, GDPR, and internal security protocols in development.

Assist in implementing data access controls and encryption mechanisms.

Team & Tech Stack
Team Composition:
Client (USA) / Ukraine-based team (2 DE, 2 DA, 1 BA).
Tech Stack:
Programming languages: Python, JavaScript, SQL.
Cloud Services: Azure (Azure Data Factory), minimal AWS usage.
ETL Tools: Airbyte, Dagster (Airflow, Azure Data Factory)
Database: SQL Server.
Reporting Tools: Power BI, Node/D3
QA: Handled by the client.

🎓 Role Requirements

✔ 3+ years of experience in Data Engineering, ETL development, and SQL.

✔ Cloud infrastructure expertise: Azure, AWS (optional).

✔Experience with data pipeline/workflow tools: Airbyte, Dagster. It would be nice to have experience with tools such as Airflow and Azure Data Factory.

✔Knowledge of Python and JavaScript programming languages.
Experience with Node.js and D3 module

✔ Knowledge of SQL Server and T-SQL.

✔ Basic knowledge of Power BI or similar reporting tools.

✔ Strong problem-solving skills and ability to work in cross-functional teams.

✔ Upper-Intermediate English for communication with the team and stakeholders.

Nice-to-Have:

➕ Experience with AI services and integrations.

➕ Experience with security & compliance in healthcare data management.

📅 Workload & Time Zone

⏳ Full-time engagement required.

🌍 It would be a great advantage if your current time zone matched the US Central Time Zone as closely as possible.

🔄 Direct communication with the client expected.

📌 Interview Process

1️. Initial screening (greenm team: 1 hour — TA and 1,5 hour lead DE)

2️. Short voice recording (2-3 min) in English (structured answers to given questions).

3️. Final interview with the client.

🚀 Join a dynamic healthcare project and contribute to building scalable data solutions!

📩 Apply now and be part of transforming healthcare analytics!