Data Engineer
Location
United States
Posted
3 days ago
Salary
0
Seniority
Mid Level
Job Description
Data Engineer
Vytalize Health
• Handle support tickets and operational issues reported by internal teams and external partners; investigate root causes and coordinate resolution with senior engineers • Perform KTLO (Keep The Lights On) tasks including monitoring pipeline health, responding to alerts, validating data quality, and investigating data anomalies • Conduct data source discovery and profiling work — examining raw data sources, documenting data structure, identifying quality issues, and recommending integration approaches • Assist with data validation and testing — writing SQL queries to validate data transformations, identifying gaps and inconsistencies, and flagging issues for review • Support data quality initiatives by running diagnostics, documenting data quality findings, and escalating issues with clear context for senior engineers • Assist in establishing and monitoring data quality metrics — working with senior engineers to define quality KPIs and track pipeline health • Help maintain and improve documentation for existing data systems, pipelines, and data sources — documenting schemas, transformation logic, and known issues • Assist senior engineers with debugging data pipeline issues — tracing data through transformations, validating intermediate outputs, and comparing expected vs. actual results • Conduct quality assurance activities — reviewing data outputs, testing transformations, and validating correctness before data reaches downstream consumers • Perform exploratory data analysis to understand data patterns, support analytics requests, and help answer business questions about data availability and quality • Learn and apply data engineering best practices including version control (Git), code review processes, and testing frameworks under guidance from senior engineers • Support infrastructure and operational tasks as assigned — assisting with deployments, maintaining environments, and supporting on-call activities • Participate in knowledge-sharing and mentorship; ask questions, document learnings, and contribute to team documentation and runbooks
Job Requirements
- Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent hands-on experience
- Strong SQL proficiency — ability to write queries to explore, validate, and analyze data
- Proficiency in Python or another programming language; comfort writing scripts and automation
- Basic understanding of data modeling, ETL/ELT concepts, and data pipeline architecture
- Familiarity with version control (Git) and collaborative development practices
- Strong communication skills; ability to document findings clearly and ask clarifying questions
- Analytical mindset and strong problem-solving skills, especially for data quality and debugging tasks
- Attention to detail and commitment to data accuracy and reliability
- Basic understanding of data quality concepts and the importance of testing and validation
- Willingness to learn from experienced engineers and grow into a full data engineer role
Benefits
- Health insurance
- Professional development opportunities
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