Senior Data Engineer: Lead Scalable Pipelines & ML

eHealthinsurance Services, Inc.; Northern (KY); Hybrid; USD 115,000 - 144,000; Full time

Benefits offered by this job

Medical, dental and vision benefits

401K with matching

Tuition reimbursement

Employee stock purchase program

Holiday and PTO

Job summary

eHealth is seeking a Senior Data Engineer to lead the design and implementation of scalable data pipelines and real-time streaming architectures in a healthcare context. You will collaborate with data scientists and software engineers to build robust data platforms and ML workflows.

The role emphasizes data quality, observability, and governance, with opportunities to influence engineering standards and drive cross-team initiatives. A strong cloud and coding foundation is essential.

Qualifications

• 5+ years of data engineering experience in a relevant field.
• Expert-level SQL for complex queries and optimization.
• Strong programming skills in Python or Scala with modern software practices.

Responsibilities

• Architect, build, and maintain scalable data pipelines and real-time streaming architectures using Spark, Kafka, dbt.
• Design and drive workflow automation with Airflow or Matillion.
• Lead production-grade ML pipelines with APIs for model predictions.
• Mentor junior and mid-level data engineers through code reviews and guidance.
• Own data quality, observability, lineage, and governance strategies.
• Collaborate with DevOps on platform architecture, performance and security/compliance.
• Evaluate new data tools and propose build-vs-buy decisions.

Skills

Advanced SQL

Python

Scala

CI/CD

Git workflows

API development

AWS

Data modeling

Data governance

Education

Bachelor's or Master's in CS/Engineering

Tools

Snowflake

BigQuery

Redshift

Databricks

dbt

Spark

Informatica

Matillion

Kafka

Kinesis

Job description

eHealth is seeking a Senior Data Engineer to lead the design and implementation of scalable data pipelines and real-time streaming architectures in a healthcare context. You will collaborate with data scientists and software engineers to build robust data platforms and ML workflows.

The role emphasizes data quality, observability, and governance, with opportunities to influence engineering standards and drive cross-team initiatives. A strong cloud and coding foundation is essential.