Data Engineer — India

BioStack Platforms; Bengaluru; On-site; INR 2,000,000 - 4,000,000; Full time

Job summary

BioStack Platforms in Bengaluru, India, is hiring a Data Engineer to own large healthcare datasets from ingestion through delivery. You will build and optimize ETL/ELT pipelines for structured and unstructured data, ensure data quality, and collaborate with ML and clinical teams.

The role requires 3+ years of experience, strong Python/SQL, and experience with Spark, Ray, DuckDB, Polars, Pandas, and cloud services (AWS/GCP/Azure). Urgent hiring; full-time on-site location in India.

Qualifications

• 3+ years of professional experience in data engineering, backend engineering, or related role.
• Strong Python and SQL skills.
• Experience building production data pipelines.
• Experience processing large datasets with Spark, Ray, DuckDB, Polars, Pandas or similar tools.
• Experience with AWS, GCP, or Azure and object storage like S3.
• Strong understanding of ETL/ELT, schemas, transformations, and data validation.

Responsibilities

• Ingest and process large datasets from hospitals, clinics, labs, and partners.
• Build pipelines for structured and unstructured healthcare data.
• Clean, normalize, transform, merge, and validate large datasets.
• Work with datasets containing millions of records.
• Build fast, reliable, reproducible ETL/ELT pipelines.
• Automate data-quality checks for missing/duplicate/corrupted records.
• Design schemas and standardized formats for heterogeneous datasets.
• Ensure secure transfer and processing of large datasets.
• Collaborate with ML, clinical, and operations teams to create AI-ready data.
• Maintain documentation around schemas, transformations, lineage, and dataset versions.
• Troubleshoot broken pipelines and data issues quickly.
• Take end-to-end ownership of data delivery.

Skills

Python

SQL

Data pipelines

Tools

Spark

Ray

DuckDB

Polars

Pandas

S3

Job description

About BioStack

BioStack 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.

Job Details

• Location: India
• Experience: 3+ years
• Employment Type: Full-time
• Hiring Priority: Urgent

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 Here

You 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.