9 days ago

Support Data Engineer

RemoteHunter

Hybrid
Full Time
$107,500
Hybrid

Job Overview

Job TitleSupport Data Engineer
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$107,500
LocationHybrid

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Job Description

About the Opportunity

The organization provides an end-to-end ecosystem designed to support Programs of All-Inclusive Care for the Elderly (PACE) in delivering care, improving financial performance, and ensuring compliance. This Support Data Engineer role replaces outdated technology with modern solutions for care coordination, risk adjustment, population health, and utilization management, focusing on operations and improving outcomes for dual-eligible seniors with complex healthcare needs.

Responsibilities

  • Own and maintain a legacy population health analytics product, focusing on backend data pipelines and the full-stack application.
  • Operate the production analytics product, managing data ingestion, transformation, orchestration, and the user interface.
  • Build, maintain, and debug backend data pipelines using Airflow, Python (Pandas, Selenium), Snowflake, dbt, and Airbyte, emphasizing data quality and performance.
  • Manage the full-stack analytics application, including backend services (Node.js) and frontend components (React).
  • Address bug fixes, operational issues, and production incidents, understanding system behavior and failure modes.
  • Investigate and resolve data quality issues, pipeline failures, and application defects with durable fixes.
  • Improve legacy codebases balancing speed, correctness, and maintainability.
  • Communicate clearly about system health, root causes, and technical tradeoffs with teams and stakeholders.

Requirements

  • Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent experience.
  • 1 to 4 years of experience as a Software Engineer or Data Engineer.
  • Proficiency in Python and experience with production data pipelines or ETL/ELT workflows.
  • Working knowledge of SQL and relational or analytical databases.
  • Exposure to backend or full-stack development, including JavaScript and Node.js.
  • Familiarity with frontend technologies like React or willingness to learn and maintain existing frontend code.
  • Basic knowledge of modern data tools such as Airflow, dbt, Snowflake, and Airbyte.
  • Ability to debug legacy systems and handle complex technical issues.
  • Strong ownership and accountability for production systems.
  • Clear written and verbal communication skills.

Preferred Qualifications

  • Experience maintaining legacy systems in production.
  • Exposure to healthcare data, analytics platforms, or regulated environments.
  • Experience working in small teams or fast-paced environments.

Benefits & Perks

  • Competitive salary and benefits package including uncapped PTO and health insurance.
  • Professional development and growth opportunities.
  • Flexible remote work environment.

Key skills/competency

  • Data Pipelines
  • ETL/ELT
  • Python
  • SQL
  • Snowflake
  • dbt
  • Airflow
  • React
  • Node.js
  • Healthcare Data

Tags:

Support Data Engineer
Data Pipelines
ETL
ELT
Population Health
Analytics
Healthcare
Full-stack
Legacy Systems
Operations
Python
SQL
Airflow
Snowflake
dbt
Airbyte
Node.js
React
JavaScript
Pandas

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How to Get Hired at RemoteHunter

  • Research RemoteHunter's values: Understand their mission in connecting talent with employers and the impact of the Support Data Engineer role on healthcare technology.
  • Tailor your resume: Highlight Python, SQL, data pipeline, and full-stack experience, specifically mentioning tools like Snowflake, dbt, and React, crucial for a Support Data Engineer.
  • Showcase problem-solving skills: Prepare examples demonstrating your ability to debug legacy systems, resolve data quality issues, and maintain production environments.
  • Emphasize communication: Practice articulating technical tradeoffs and system health clearly, as this is vital for the Support Data Engineer role at RemoteHunter.
  • Prepare for technical interviews: Brush up on data engineering fundamentals, SQL querying, Python scripting, and your familiarity with modern data stack tools.

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