Data Engineer I IS - Remote
RemoteHunter · United States
- Hybrid
- Full-time
- $81,940 / year
- United States
Tailored resume — keyword-matched to this role.
Hiring manager — we find who's hiring.
Intro email — drafted to reach them directly.
Job highlights
- Design and develop scalable data applications.
- Automate and monitor data pipelines.
- Ensure data reliability and security.
- Collaborate with product and analytics teams.
- Support healthcare workflows with data.
About the role
About Our Client
The organization operates in the healthcare sector, addressing the challenges of managing and utilizing large-scale clinical and operational data across a comprehensive health system. It provides data-centric solutions that support healthcare workflows through cloud technologies, big data platforms, and data science methodologies. With a network spanning over 50 hospitals and 1,000 clinics across multiple states, the program aims to improve care delivery for vulnerable populations while advancing best practices in healthcare data management.
About the Opportunity
The Data Engineer I is responsible for designing and developing scalable data applications that support clinical and operational workflows within the healthcare system. This role ensures the reliability, security, and cost-efficiency of the enterprise data platform by automating and monitoring data pipelines, resolving incidents, and collaborating with product and analytics teams. The position contributes by maintaining high data quality and operational standards to meet strict service level agreements.
Responsibilities
- Design and develop scalable data pipelines and transformation processes
- Automate and monitor batch and streaming ELT/ETL pipelines across cloud services and Snowflake
- Perform triage for pipeline failures, conduct root-cause analysis, and reduce mean time to recovery
- Orchestrate schedules and manage data connectors
- Build operational automation using SQL, Python, and shell scripting
- Implement observability with logging, alerting, data-quality checks, and runbooks
- Optimize Snowflake performance and manage costs
- Enforce access controls and manage secrets to support compliance and audits
- Partner with product and analytics teams, document procedures, and provide on-call support
Requirements
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience
- Minimum one year of experience with Snowflake, CTRL-M, and Azure Data Factory
- Strong SQL skills and hands-on experience with Python and shell scripting on Linux
- Experience with cloud computing, data warehousing, and relational database fundamentals
- Knowledge of OLAP/dimensional modeling and semi/unstructured data formats
- Familiarity with open-source ELT/ETL tools, Git workflows, and CI/CD practices for data deployments
- Experience building and managing data ingestion pipelines into cloud data platforms
- Working knowledge of Snowflake database objects and basic query optimization
Key skills/competency
- Data Engineering
- Snowflake
- Azure Data Factory
- Python
- SQL
- ETL/ELT
- Data Pipelines
- Cloud Computing
- Data Warehousing
- Shell Scripting
Skills & topics
- Data Engineer
- Snowflake
- Azure Data Factory
- Python
- SQL
- ETL
- ELT
- Data Pipelines
- Cloud Computing
- Data Warehousing
- Healthcare IT
- Remote Job
- Entry Level Data Engineer
How to get hired
- Tailor your resume: Highlight experience with Snowflake, Python, SQL, and Azure Data Factory, matching keywords from the job description.
- Showcase cloud skills: Emphasize your background in cloud computing, data warehousing, and data ingestion pipelines.
- Demonstrate problem-solving: Prepare examples of pipeline failure analysis and incident resolution for technical interviews.
- Understand healthcare data: Be ready to discuss the unique challenges and requirements of healthcare data management.
- Prepare for technical tests: Expect coding challenges in SQL and Python, and questions on data modeling and optimization.
Technical preparation
Practice SQL queries for data manipulation.,Write Python scripts for data automation.,Familiarize with Snowflake architecture and performance.,Understand Azure Data Factory pipeline creation.
Behavioral questions
Describe a complex data pipeline failure.,How do you ensure data quality?,How do you collaborate with analytics teams?,Explain your experience with remote work.
Frequently asked questions
- What is the work arrangement for the Data Engineer I role at RemoteHunter?
- The Data Engineer I position is a fully remote role, allowing you to work from any location. RemoteHunter focuses on connecting candidates with employers for remote opportunities.
- What is the primary technology stack for this Data Engineer I position?
- Key technologies for this role include Snowflake, Azure Data Factory, Python, and strong SQL skills. Experience with CTRL-M and shell scripting on Linux is also required.
- Does this Data Engineer I role require a specific degree?
- A Bachelor's degree in Computer Science, Engineering, or equivalent experience is preferred. However, equivalent experience in the field can also be considered.
- What kind of experience is needed for the Data Engineer I role?
- You'll need at least one year of experience with Snowflake, CTRL-M, and Azure Data Factory, along with hands-on experience in Python, shell scripting, cloud computing, and data warehousing.
- How does RemoteHunter help me get hired for this Data Engineer I position?
- RemoteHunter acts as a connector, helping you discover this role and guiding you to complete your application directly through the hiring company’s career page or ATS. We facilitate the connection to the employer.
- What are the core responsibilities of a Data Engineer I in this healthcare role?
- The core responsibilities include designing and developing scalable data pipelines, automating and monitoring ELT/ETL processes, troubleshooting pipeline failures, optimizing Snowflake performance, and ensuring data quality and security within a healthcare system.
- Are there opportunities for professional growth in this Data Engineer I role?
- While not explicitly stated, roles in data engineering within large healthcare systems often offer opportunities for growth as you gain experience with complex data challenges and contribute to critical healthcare initiatives.