Data Engineer in ESJ Equities

At the intersection of technology and healthcare, we envision a future where medical billing is not just a necessary task but an opportunity for innovation and progress. We believe that through the power of artificial intelligence and data aggregation, we can create a platform that not only streamlines the billing process but also empowers healthcare providers to focus on what truly matters - delivering the best possible care to their patients.

We are not content with simply improving the status quo, we are driven to completely disrupt the industry and pave the way for a new era of healthcare. We want to empower healthcare providers and their patients with the tools and information they need to make informed decisions. We want to create a platform that is so efficient and user-friendly that it becomes an integral part of the healthcare ecosystem.

1. Data Collection & Integration: Extract, collect, and integrate data from diverse sources, ensuring data is clean, reliable, and of high quality.
2. Data Architecture & Database Management: Design and implement database and data warehousing solutions to store and process data efficiently. Work closely with other teams to optimize database queries and structures.
3. ETL Processes: Develop and maintain scalable ETL processes to ensure the data pipeline remains robust and efficient.
4. Data Security: Ensure that all data storage and processing mechanisms comply with security standards, especially HIPAA and OAuth 2.0.
5. Collaboration: Collaborate with data scientists, BI analysts, and other stakeholders to ensure data requirements are met and facilitate data-driven decision-making.
6. Continuous Improvement: Monitor system performance, identify areas of improvement, and implement upgrades as necessary.
7. Documentation: Maintain detailed documentation on data sources, data transformation logic, and related ETL processes.

1. Educational Background: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
2. Experience: Minimum of 3 years' experience in a data engineering role, preferably within the medical or healthcare sector.
3. Technical Proficiency: Strong proficiency in SQL and Python required, and experience with tools like Jira, Bitbucket, and Confluence preferred.
4. Knowledge of Standards: Familiarity with data security standards, especially HIPAA and OAuth 2.0.

1. Real-time Data Processing: Experience in real-time data processing and stream analytics.
2. Machine Learning Integration: Familiarity with integrating data for machine learning model training and deployment.
3. Strong Analytical Skills: Ability to understand complex data structures, and identify patterns and anomalies.
4. Teamwork & Collaboration: Strong interpersonal and teamwork skills.

Competitive salary paid in USD.