Senior Data Engineer

eHealth, Inc.

. Serve as a subject-matter expert on the data ecosystem, including internal systems and third-party data sources .

Posted 9/23/2026full-timeRemote • United StatesSenior💰 $115,000 - $143,800 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in architecting and maintaining scalable data pipelines and real-time streaming architectures, with a strong focus on data quality, governance, and observability. Proficient in leveraging modern ETL/ELT frameworks and cloud-native platforms to drive automation and optimize data workflows.

Highest-signal resume keywords

Data Pipeline ArchitectureExpert-Level SQLPython ProgrammingCloud-Native Data PlatformsData Governance

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringETL/ELT FrameworksData ModelingAPI DevelopmentCI/CDPerformance TuningNoSQL DatabasesCloud PlatformsEvent-Driven ArchitecturesMachine Learning Pipelines

Soft Skills

MentoringCommunicationTechnical Guidance

Tools & Technologies

SparkKafkaDbtApache AirflowMatillionGitHub CopilotDatabricksDockerKubernetesTableau

Industry Keywords

HealthcareEHRHIPAASOC 2Data Observability

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSBigQueryCassandraCloudDockerETLInformaticaKafkaKubernetesMatillionMongoDBNoSQLPythonScalaSparkSQLTableau

About the role

Key responsibilities & impact

Serve as a subject-matter expert on the data ecosystem, including internal systems and third-party data sources
Guide architectural decisions across teams
Architect, build, and maintain scalable data pipelines and real-time streaming architectures using frameworks such as Spark, Kafka, and dbt
Design and drive adoption of workflow automation and orchestration standards using Apache Airflow or Matillion
Lead technical design for production-grade ML pipelines and APIs serving model predictions
Leverage AI-assisted development tools such as GitHub Copilot, Claude Code, and Cursor for pipeline development, code review, and testing
Establish team norms for effective and responsible use of AI-assisted development tools
Own data quality, observability, lineage, and governance strategy
Define monitoring, alerting, and metadata tracking best practices
Drive logical and physical data modeling efforts and schema design decisions
Partner with DevOps and infrastructure teams on platform architecture, performance optimization, and security/compliance strategy
Mentor junior and mid-level data engineers through code review, technical guidance, and knowledge-sharing
Evaluate emerging data tools and technologies
Make build-vs-buy and adoption recommendations to engineering leadership
Demonstrate eHealth's values in behaviors, practices, and decisions

Requirements

What you’ll need

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
5+ years of related data engineering experience with a Bachelor's degree; 3+ years with a Master's degree; or an equivalent combination of education and relevant experience
Expert-level SQL for complex query development, optimization, and performance tuning across large datasets
Strong programming skills in Python or Scala
Experience with CI/CD, git workflows, testing, code review, and API development
Experience architecting solutions on a cloud-native data platform such as Snowflake, BigQuery, Redshift, or Databricks
Deep working knowledge of modern ETL/ELT frameworks such as dbt, Spark, Informatica, or Matillion
Experience with NoSQL databases such as MongoDB, Cassandra, or Hive
Substantial experience with cloud platforms, preferably AWS, including S3, Glue, Lambda, Redshift, or EMR
Strong command of data modeling, data governance, and security principles
Demonstrated experience mentoring engineers and/or leading technical initiatives
Excellent communication skills
Preferred: Hands-on experience with Databricks and Delta Lake
Preferred: Deep knowledge of event-driven architectures and tools such as Kafka or Kinesis
Preferred: Experience designing RESTful APIs for data delivery and ML model serving
Preferred: Experience with Docker and Kubernetes in production
Preferred: Visualization experience with Tableau, Power BI, or Looker
Preferred: Exposure to healthcare or health tech, including EHR, claims data, or call center analytics
Preferred: Experience operating in regulated environments such as HIPAA or SOC 2
Preferred: Track record of driving automation, data observability, and proactive monitoring initiatives

Benefits

Comp & perks

Medical, dental and vision beginning on your first day of employment
401K with matching
Tuition reimbursement
Employee stock purchase program
12 company paid holidays
Flexible time off (PTO for non-exempt)
Annual performance bonus
Professional and personal wellness support through the total rewards package