Data Engineer

Job Title:

Data Engineer – Medical Imaging & Health Data

Experience

Required:

Minimum 3 Years

Location:

Chennai

Employment Type:

Full-time

About the Role

We are seeking a skilled and experienced Data Engineer with a strong background in

medical imaging and healthcare data to join our growing team. The role involves building

scalable and secure data infrastructure for powering clinical research, AI-based diagnostics,

and healthcare analytics.

This role is ideal for someone comfortable working with diverse data types, including medical

images, clinical records, and time-series data, and who has experience with modern data

lakes, streaming platforms, and distributed databases.

Key Responsibilities

● Ingest, process, and manage large-scale medical imaging datasets (e.g., MRI, CT

scans, pathology slides) in DICOM and non-DICOM formats.

● Develop robust ETL/ELT pipelines to extract and transform healthcare data from EHRs,

PACS, RIS, and medical registries using tools like Apache NiFi, Airflow, or Dagster.

● Build streaming and event-driven pipelines using Kafka, Rabbit

MQ, and other

messaging systems.

● Design scalable storage systems for structured, unstructured, and semi-structured data

using data lakes (e.g., Apache Hudi, Iceberg, Delta Lake) over Amazon S3 or MinIO.

● Implement distributed databases (e.g., Cassandra, Click House, Mongo

DB,

Elastic Search) for various analytical workloads.

● Collaborate with clinicians, researchers, and ML teams to prepare datasets for

downstream AI/ML pipelines and analytics platforms.

Integrate graph databases for modeling complex biomedical relationships.

● Ensure data security, governance, anonymization, and compliance with HIPAA, GDPR,

and related healthcare standards.

● Enable data observability, monitoring, and audit trails for all pipeline components.

● Work with query engines such as Trino for federated query access across systems.

● Support data versioning and reproducibility using DVC.

● Perform data migrations and query optimization across polyglot data systems.

Must-Have Skills & Experience

● Bachelor’s or Master’s in Computer Science, Biomedical Engineering, Health

Informatics, or a related field.

● Minimum 3 years of experience as a Data Engineer in the healthcare or biomedical

domain.

● Expertise in Python, SQL, and handling medical imaging with libraries like pydicom,

Simple

ITK, or Nibabel.

● Solid understanding of healthcare interoperability standards (DICOM, HL7, FHIR,

OMOP).

● Hands-on with distributed systems and databases like Cassandra, Mongo

DB,

Elastic Search, Click House, Timescale

DB, and Redis.

● Experience with Apache Spark, Apache Kafka, and streaming/event-driven

architectures.

● Familiar with data lakes (Apache Hudi, Iceberg, Delta Lake) and cloud/object storage

(Amazon S3, MinIO).

Proficient with ETL orchestration using Airflow, Dagster, or Apache NiFi.

● Comfortable with messaging queues (Rabbit

MQ).

● Strong foundation in data security, privacy, and regulatory compliance (HIPAA, GDPR).

Good-to-Have Skills

● Experience working with time-series databases:
Influx

DB, Timescale

DB, Quest

DB.

● Experience with graph databases like Orient

DB, Raven

DB, or Neo4j.

● Exposure to SQL/No

SQL ecosystems:
MySQL, Postgre

SQL, Maria

DB, HBase,

Bytebase.

● Familiarity with Elasticsearch for indexing and search over medical datasets.

● Prior involvement in MLOps, feature stores, or AI/ML lifecycle integration.

● Understanding of data observability and monitoring tools for pipelines.

● Experience with data migration strategies and query performance tuning.

● Exposure to clinical registries, cohort builders, or clinical trial platforms.

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