Senior Data Engineer / Data Architect

About AccuData Analytics

AccuData Analytics Pvt. Ltd. partners with US healthcare organizations to build secure, scalable, AI-driven digital health platforms, with expertise in cloud infrastructure, data engineering, AI systems, and healthcare compliance-first

Architecture.

About the role

We're hiring a Data Engineer to build and run ETL pipelines that migrate healthcare data from legacy source systems into a backend platform via REST APIs and direct

PostgreSQL writes into tenant-isolated schemas.

What you'll do

Build and maintain Python ETL pipelines that read CSV/Excel source exports and migrate them into a backend system via REST API calls and direct PostgreSQL inserts

Design idempotent, rerun-safe migration commands (dry-run modes, mapping/result

CSVs, signature-based drift detection)

Handle real-world messy data: inconsistent column naming, duplicate records, missing fields, normalization of phone/date/ID formats

Write and maintain validation layers pre-migration contract checks and post-migration read-only reconciliation

Work with multi-tenant, schema-per-tenant PostgreSQL architecture

Collaborate closely with the technical lead on migration scope, sequencing, and safety guardrails for sensitive data

What we're looking for

5-10 years of experience in Python data engineering / ETL development

Strong SQL and hands-on experience with PostgreSQL (psycopg2 or similar)

Experience consuming/calling REST APIs (auth, pagination, error handling, retries)

Comfortable working with large CSV/tabular datasets and writing data validation logic

Understanding of idempotency, batch processing, and safe rerun design in data pipelines

Bonus: experience with healthcare or other regulated/sensitive data domains, or multi-tenant systems

Tech stack

Language:

Python 3.10+

Database:

PostgreSQL (psycopg2, multi-tenant/schema-per-tenant, batch inserts with execute

_

values

)

API/HTTP:

REST APIs,

requests

, Bearer token auth

Config/Env:

python-dotenv

,

.env

-based configuration

Testing:

unittest

/

pytest

Version control:

Git

Cloud (nice to have):

AWS (Secrets Manager, EKS/ECR)

Backend frameworks (nice to have):

Django REST Framework or FastAPI

Optional / good to have (pipeline evolution)

Workflow orchestration Airflow, Prefect, or Dagster

Data validation frameworks Great Expectations or Pandera

Containerization Docker

Async/background processing Celery + Redis .