Data Engineer — India

Location: India

Experience: 3+ years

Employment Type: Full-time

Hiring Priority: Urgent

About BioStackBioStack is building the data and environment layer for medical AI. We work with large-scale healthcare datasets across clinical records, imaging, pathology, labs, genomics, and longitudinal patient data.

We are urgently hiring a Data Engineer who can take ownership of large datasets from ingestion through final delivery.

What You’ll Do

• Ingest and process large datasets from hospitals, clinics, labs, research organizations, and data partners.
• Build pipelines for structured and unstructured healthcare data.
• Clean, normalize, transform, merge, and validate large datasets.
• Work with datasets containing millions of records and files.
• Build ETL/ELT pipelines that are fast, reliable, and reproducible.
• Automate data-quality checks for missing, duplicate, inconsistent, or corrupted records.
• Design schemas and standardized formats for heterogeneous datasets.
• Build workflows for securely transferring and processing large datasets.
• Work with ML, clinical, and operations teams to turn raw data into AI-ready datasets.
• Maintain documentation around schemas, transformations, lineage, and dataset versions.
• Troubleshoot broken pipelines and unexpected data issues quickly.
• Take end-to-end ownership of data delivery.

Requirements

• 3+ years of professional experience in data engineering, backend engineering, infrastructure, or a related role.
• Strong Python skills.
• Strong SQL skills.
• Experience building production data pipelines.
• Experience processing large datasets using tools such as Spark, Ray, DuckDB, Polars, Pandas, or similar technologies.
• Experience with AWS, GCP, or Azure.
• Experience with object storage such as S3.
• Strong understanding of ETL/ELT, schemas, transformations, and data validation.
• Ability to work with messy, incomplete, and inconsistent real-world data.
• Strong debugging and problem-solving skills.
• Ability to work independently and move quickly.

Strongly Preferred

• Experience with PII/PHI detection, redaction, or de-identification.
• Experience working with healthcare or sensitive datasets.
• Familiarity with HIPAA or healthcare data privacy requirements.
• Experience building automated redaction or anonymization pipelines.
• Experience with EHR, clinical, imaging, or biomedical datasets.

Nice to Have

• Familiarity with FHIR, HL7, DICOM, ICD, CPT, LOINC, or SNOMED.
• Experience processing medical imaging datasets.
• Experience with clinical text or NLP pipelines.
• Experience preparing datasets for ML or LLM training.
• Experience working at an early-stage startup.

Who Will Do Well HereYou should be comfortable receiving a raw dataset with millions of files, inconsistent formatting, missing fields, duplicate records, and sensitive information—and figuring out how to make it usable.

We value people who are highly hands-on, move fast, and take ownership without waiting for perfectly defined requirements.

• This is an urgent requirement. Candidates who can join immediately or within a short notice period will be prioritized.