Senior Software Engineer - Data Engineering

Remote

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Healthcare TechnologyIndustries

Requirements

Candidates should have 5+ years of hands-on experience in data engineering, with a strong focus on building and maintaining scalable and reliable data pipelines (ETL/ELT). Proven experience with data warehousing concepts, data modeling (e.g., dimensional, relational), and building analytical datasets is required. Proficiency in Python and SQL is necessary, along with experience with data pipelining tools like Spark/PySpark and dbt, and platforms like AWS, Databricks, or Google Bigquery. Experience with data governance principles, data quality management, and data security is also required. Experience implementing monitoring and alerting for data pipelines is beneficial, as is familiarity with BI tools (Looker and LookML) and how data is consumed for analytics and reporting. Proficiency in version control (Github) and CI/CD tools (CircleCI) is expected, along with experience working with non-technical teammates to identify dataset requirements.

Responsibilities

The Senior Software Engineer - Data Engineering will lead the design, development, and refactoring of critical data pipelines to reduce failures and improve efficiency. They will implement comprehensive monitoring, alerting, and service level agreement tracking to achieve and maintain high operational uptime. The role involves resolving data pipeline issues, contributing to faster incident resolution, and contributing to the development, implementation, and adoption of data governance standards across critical datasets. The engineer will ensure data quality and integrity throughout the data lifecycle, enforce governance standards on core pipelines, participate in the redesign and deployment of core subject areas within our analytical data model to improve clarity, utility, and support business reporting needs. They will establish dashboard curation standards to improve usability and user satisfaction, eliminate unused or inefficient tasks within our data processing frameworks, develop structured data extractors for various application use cases, contribute to compute cost reduction efforts through task reconfiguration and the implementation of efficient incremental data processing strategies, and develop mechanisms to make application engineers aware of potential breaking changes to data schemas.

Skills

Python

SQL

Spark

PySpark

dbt

Data Pipelines

Data Warehousing

Data Modeling

ETL/ELT

Data Governance

Data Quality

Data Lifecycle Management

Monitoring and Alerting

Cost Optimization

Analytical Datasets

Included Health

Healthcare advocacy and specialized care services

About Included Health

Included Health focuses on enhancing the healthcare experience for individuals who often face challenges in accessing quality care. The company provides a variety of services, including primary care, behavioral health, and virtual care, ensuring that members receive timely and appropriate treatment. Their model emphasizes 24/7 on-demand care with a diverse group of providers, allowing for personalized support tailored to complex health needs. Unlike many competitors, Included Health prioritizes underserved populations and partners with employers and consultants to deliver comprehensive healthcare solutions that not only improve health outcomes but also help reduce costs. The ultimate goal of Included Health is to make quality healthcare accessible and understandable for everyone, particularly those who have been overlooked by traditional healthcare systems.

San Francisco, CaliforniaHeadquarters

2020Year Founded

$337.5MTotal Funding

GROWTH_EQUITY_VCCompany Stage

HealthcareIndustries

51-200Employees