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, RabbitMQ, 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, ClickHouse, MongoDB,

ElasticSearch) 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

Bachelors or Masters 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,

SimpleITK, or Nibabel.

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

OMOP).

Hands-on with distributed systems and databases like Cassandra, MongoDB,

ElasticSearch, ClickHouse, TimescaleDB, 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 (RabbitMQ).

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

Good-to-Have Skills

Experience working with time-series databases: InfluxDB, TimescaleDB, QuestDB.

Experience with graph databases like OrientDB, RavenDB, or Neo4j.

Exposure to SQL/NoSQL ecosystems: MySQL, PostgreSQL, MariaDB, 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.