Data Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Manage support tickets and operational challenges reported by internal teams and external partners; investigate root causes and collaborate with senior engineers for resolution.

• Execute KTLO (Keep The Lights On) tasks, including monitoring pipeline health, responding to alerts, validating data quality, and examining data anomalies.

• Conduct data source discovery and profiling activities—analyzing raw data sources, documenting data structures, identifying quality concerns, and suggesting integration methods.

• Aid in data validation and testing—writing SQL queries to verify data transformations, identifying gaps and inconsistencies, and reporting issues for evaluation.

• Support data quality initiatives by running diagnostics, documenting findings related to data quality, and escalating issues with detailed context for senior engineers.

• Assist in establishing and tracking data quality metrics—collaborating with senior engineers to define quality KPIs and monitor pipeline health.

• Help maintain and enhance documentation for existing data systems, pipelines, and data sources—documenting schemas, transformation logic, and known issues.

• Assist senior engineers in troubleshooting data pipeline problems—tracing data through transformations, validating intermediate outputs, and comparing expected versus actual results.

• Conduct quality assurance tasks—reviewing data outputs, testing transformations, and ensuring correctness before data reaches downstream consumers.

• Perform exploratory data analysis to uncover data patterns, support analytics requests, and address business inquiries regarding data availability and quality.

• Learn and implement data engineering best practices, including version control (Git), code review processes, and testing frameworks, under the guidance of senior engineers.

• Support infrastructure and operational tasks as needed—assisting with deployments, maintaining environments, and participating in on-call activities.

• Engage in knowledge-sharing and mentorship; ask questions, document insights, and contribute to team documentation and runbooks.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent hands-on experience.

• Strong SQL skills—capable of writing queries to explore, validate, and analyze data.

• Proficient in Python or another programming language; comfortable 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.

• Excellent communication skills; able to document findings clearly and ask clarifying questions.

• Analytical mindset with strong problem-solving abilities, particularly for data quality and debugging tasks.

• Attention to detail and a commitment to data accuracy and reliability.

• Basic understanding of data quality concepts and the significance of testing and validation.

• Eagerness to learn from experienced engineers and evolve into a full data engineer role.

🏝️ Benefits

• Health insurance

• Professional development opportunities