The Role

As a Data Ingestion Engineer, you will design and build the systems that pull health data from a diverse and growing set of sources — wearables (Apple Health, Fitbit, Oura, Whoop, etc.), connected medical devices (glucose monitors, BP cuffs, ECG patches), lab and diagnostic feeds, EHR / HL7-FHIR systems, and patient-reported data — and land it reliably into Nickel's platform in a form doctors and downstream systems can trust.

You will work at the intersection of high-volume streaming data, healthcare interoperability standards, and strict data integrity requirements — building pipelines where "mostly correct" is not good enough, because a doctor may be making a call based on your data.

What You'll Do

- Design, build, and operate ingestion pipelines for structured and unstructured health data from multiple device APIs, third-party health platforms, and clinical data sources
- Build integrations with wearable/device SDKs and health data standards (Apple HealthKit, Google Health Connect, HL7/FHIR, DICOM where relevant)
- Architect for reliability at the edges — handling intermittent connectivity, device data gaps, duplicate/out-of-order events, and vendor API instability gracefully
- Implement data validation, normalization, and schema management so heterogeneous sources land in a consistent, queryable format
- Build real-time and batch ingestion paths depending on data criticality (e.g., an arrhythmia alert vs. a weekly step count)
- Work closely with platform, ML, and clinical product teams to understand what "usable" data looks like for diagnostic and care-decision use cases
- Own data quality, lineage,



and observability for your pipelines — you'll know when something's wrong before a doctor does
- Implement ingestion in a way that's compliant with healthcare data privacy requirements (HIPAA and equivalent Indian data protection standards)

What We're Looking For

- 3–7 years of experience building data pipelines, ideally with high-volume, real-time, or IoT/device data
- Strong programming skills in Python, Go, or Java, with production experience in distributed data systems
- Hands-on experience with streaming/event infrastructure (Kafka, Kinesis, Pub/Sub, or similar)
- Experience with API integrations at scale — OAuth flows, rate limiting, retry/backoff strategies, webhook handling
- Solid understanding of data modeling and schema design for messy, multi-source data
- Exposure to healthcare data standards (HL7, FHIR, DICOM) is a strong plus — not mandatory, but a fast-track signal
- Experience with cloud-native data infra (AWS/GCP, tools like Airflow, dbt, Spark, or similar)
- A bias toward reliability and correctness over cleverness — this is data that informs medical decisions
- Comfort working in a 0-to-1 setting: this team is being built now, so you're shaping the architecture, not inheriting it

Why This Role

- You're not integrating "some device" — you're building the layer that makes continuous, diagnostics-led care technically possible
- Ground-floor architectural ownership: the ingestion patterns you set now become the platform's data spine
- Backed by an eight-figure raise and a founding team with a track record — startup pace, with real capital behind it
- India isn't a delivery arm here — this is the core build team for Nickel's platform

📌 Data Ingestion Engineer (Bengaluru)
🏢 Actualize
📍 Bengaluru