Data Engineer at Hive Health

Pasig, Metro Manila, Philippines -

Full Time

Start Date

Immediate

Expiry Date

22 Mar, 26

Salary

0.0

Posted On

22 Dec, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SQL, Python, JavaScript, Data Pipelines, Data Modeling, Technical Requirements Gathering, Problem-Solving, Attention to Detail, Communication Skills, Healthcare Data, Cloud Environments, DevOps Practices, Quality Assurance, AI, Machine Learning, Data Integration, Observability

Industry

Hospitals and Health Care

Description

Ready to make an impact? At Hive Health and HPPI, a subsidiary of Hive Health, we’re on a mission to make healthcare radically more accessible for all—and we need passionate, driven individuals to help us make it happen. If you thrive in a fast-paced, innovative environment and want to work on solutions that truly matter, we’d love to meet you! As a Data Engineer, you have a unique opportunity to join a dynamic team where you can significantly impact the healthcare journey of our members. Beyond building ETL pipelines and maintaining our data platform, you will play a key role in building digital infrastructure to help make healthcare more accessible, specifically in data integrations and observability for data quality. Working with cross-functional teams, you will gain insights into how HMOs operate and use that knowledge to expand our services to small and medium-sized businesses, which are vital to the Philippine economy. Location This is a hybrid role based in Metro Manila, Philippines, subject to change based on business needs. You must be able to commute to our office in the Ortigas area at least once per week. Responsibilities Build and maintain robust data systems for collecting, transforming, and storing complex healthcare and financial data. This may include writing short API call scripts, enhancing and maintaining data warehousing systems, and building end to end data collection pipelines. Implement automated API-based workflows that increase operational efficiencies for Hive’s stakeholders (patients, healthcare providers, employers, and internal operation teams) for implementation of single customer view and utilization management Communicate clearly and concisely technical information to non-technical stakeholders Perform query-based data exploration in SQL or Python to catalog data, maintain data dictionary, and move company towards self-serve model for dashboards. Qualifications Experience as a developer, with exposure to data pipelines or data-intensive systems. Open to fresh graduates and junior candidates. Proficiency in SQL and at least one other programming language, preferably Python or JavaScript (e.g. NodeJS). Strong understanding of software design fundamentals and the ability to design scalable systems (e.g., data modeling, technical requirements gathering). High attention to detail and quality control, with a focus on writing readable code and following engineering best practices. Familiarity with distributed version control systems and UNIX-like operating systems, such as Git and Ubuntu, is required. Excellent written communication skills, crucial for our hybrid work environment and asynchronous communications. Eagerness to learn new skills and tackle challenges related to healthcare data. Strong problem-solving skills and initiative to identify and solve undefined problems systematically. Bonus Qualifications Experience with cloud environments like Google Cloud Platform, AWS, and Azure (Hive uses GCP). Domain-specific knowledge in healthcare, such as working with medical data (e.g. FHIR, ICD-10) and implementing customer service workflows (e.g., setting up and configuring CRMs). Interest in using AI and Machine Learning for healthcare applications (e.g., LLMs, Document Intelligence, Medical Standardization). Knowledge of quality assurance practices, including end-to-end testing and integration testing. Experience with DevOps practices and tools (e.g. CI/CD, Logging, Observability). Knowledge of responsible technology practices, including health data governance. Benefits & Perks Join a founding team transforming healthcare in the Philippines and beyond. Comprehensive healthcare benefits. Hybrid work flexibility and paid time off. Career development and mentorship opportunities. Access to global tech and advisory support from institutions like Harvard and Stanford. Interview Process We are committed to fair and equitable hiring and aim to be transparent about our interview process. After your introductory interview, the process typically takes two to four weeks and consists of four conversations totaling about five hours. Introductory Interview: A preliminary conversation to understand your background and fit for the role (30 minutes; Google Meet). Take-home Exam (72 hours max): A take-home assignment to assess your technical skills and problem-solving abilities. Technical Interview: An in-depth discussion of your technical skills, problem-solving abilities, and communication skills, including systems design (60 minutes; Google Meet). Final Interview with Founders: A conversation with our founders to discuss your vision, cultural fit, and long-term goals (45 minutes; Google Meet). We recognize that individuals from diverse backgrounds may interpret job postings differently. If you do not meet all qualifications but believe you would be a great fit, please apply and share more in your application. Join our team as we revolutionalize healthcare in the Philippines—and beyond! ✨ Day 1 benefits for full-time employees – because we practice what we preach! Enjoy comprehensive healthcare coverage for you and your dependent, and paid time off from the start. 🚀 Grow with us – mentorship, career development, and learning opportunities to help you thrive. 🌍 Global connections – gain insights and support from top minds at Harvard, Stanford, and beyond.

Responsibilities

Build and maintain robust data systems for healthcare and financial data, including ETL pipelines and data warehousing. Collaborate with cross-functional teams to enhance data integrations and ensure data quality.