Senior Cloud Data Engineer — Healthcare Data Platform

Socket.dev; Elmwood Park (NJ); Hybrid; USD 130,000 - 170,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Life insurance

Long-term disability

401k matching

Work-life balance

Volunteer program

Flexible hours

Remote work options

Employee discounts

Parental leave

Gym stipend

Job summary

ELLKAY is seeking a Senior Cloud Data Engineer to design, build, and operate cloud-native data pipelines that ingest, cleanse, normalize, and deliver healthcare data at scale. You will collaborate with architecture, engineering, data governance, QA and product teams to modernize legacy point-to-point integrations into a secure, scalable data platform.

You will lead batch and streaming workloads with Spark, Databricks, Airflow and dbt; process HL7, FHIR, X12/EDI data; and implement lakehouse

Qualifications

• 5+ years of data engineering experience, including 2+ years building cloud-native solutions on AWS, Azure, or GCP.
• Strong experience with Python and SQL and distributed data-processing technologies such as Apache Spark or Databricks.
• Experience with orchestration and transformation tools such as Airflow, dbt, Prefect, or Dagster.
• Experience with cloud storage/lakehouse technologies such as S3, ADLS, Delta Lake, Apache Iceberg, or Hudi.
• Experience with a modern data warehouse such as Snowflake, Redshift, BigQuery, or Synapse.
• Experience with streaming/event-driven technologies such as Kafka, Kinesis, SQS/EventBridge, RabbitMQ, Amazon MQ, or Azure Event Hubs.
• Familiarity with Docker, Kubernetes, Terraform, CI/CD, and automated testing.
• Understanding of data quality, de-duplication, master/reference data, security, and governance.

Responsibilities

• Build scalable data pipelines for batch and streaming workloads using Spark, Databricks, Airflow, and dbt.
• Process healthcare data including HL7, FHIR, X12/EDI, CCD/CCDA, and flat-file formats.
• Build cloud lakehouse solutions using S3/ADLS, Delta Lake, Apache Iceberg, or Hudi, along with modern cloud data warehouses i.e. Snowflake, Redshift.
• Improve data quality through automated validation, cleansing, de-duplication, schema validation, and quarantine workflows.
• Support identity resolution and master data by integrating patient/member, provider, subscriber, and reference data with MPI/EMPI capabilities.
• Modernize legacy integrations into reusable, configuration-driven, event-based, streaming, and API-based patterns.
• Build for production reliability with monitoring, alerting, audit logging, data lineage, security, and operational observability.
• Collaborate across teams to translate architecture into well-tested, production-grade solutions that meet healthcare security and compliance requirements.

Skills

Python

SQL

Spark/Databricks

Airflow

dbt

FHIR/HL7

Cloud (AWS/Azure/GCP)

Docker/Kubernetes

Data governance

Security/compliance

Tools

Snowflake

Redshift

Delta Lake

Iceberg

S3/ADLS

Kafka

Kinesis

Job description

ELLKAY is seeking a Senior Cloud Data Engineer to design, build, and operate cloud-native data pipelines that ingest, cleanse, normalize, and deliver healthcare data at scale. You will collaborate with architecture, engineering, data governance, QA and product teams to modernize legacy point-to-point integrations into a secure, scalable data platform.

You will lead batch and streaming workloads with Spark, Databricks, Airflow and dbt; process HL7, FHIR, X12/EDI data; and implement lakehouse