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MEM · 3 hours ago

Data Engineer I (Remote)

United States

Full-time

Remote

Entry Level

1+ years exp

MEM Insurance is seeking a Data Engineer to join their dynamic team, focusing on building robust data systems that drive analytics and innovation. The role involves designing and optimizing data pipelines, integrating systems, and ensuring data quality to support data science, analytics, and software delivery.

Fleet ManagementHealth InsuranceInsurance

Responsibilities

Data Pipeline Development & Optimization

Work with the data engineering team to design, build, and optimize scalable data pipelines that extract, transform, and load (ETL) data from various sources into the company’s data infrastructure, ensuring data is accurate, accessible, and ready for downstream processes. This includes working with both batch and real-time (streaming) data flows

With guidance from senior members of the Data Engineering team, periodically assess existing data workflows, pipelines, and infrastructure to identify bottlenecks, inefficiencies, or areas where performance can be improved. This may involve tuning queries, optimizing ETL processes, refactoring code, or implementing new tools and technologies to enhance overall data performance

Participate in an on-call rotation to monitor, troubleshoot, and resolve issues related to overnight data processing jobs. This includes ensuring nightly ETL processes, batch jobs, and other critical data workflows are running smoothly and addressing any failures or delays in a timely manner to minimize business disruption

Implement APIs and other integration tools to support data ingestion from multiple systems, enabling seamless data movement across platforms, applications, and third-party services

Work closely with other Data Engineers, software engineers, and product development teams to ensure the necessary data pipelines, APIs, and databases are available and integrated into the company’s applications and products. Provide guidance and troubleshooting assistance related to data needs during the software development lifecycle, including testing and deployment stages

Collaborate with cross-functional and delivery team members, including analysts, data scientists, and business units, to create well-structured, accurate, and efficient data sets that meet reporting, dashboarding, and analytical needs. Ensure the data sets are tailored for ease of use and optimized for performance in reporting tools

Ensure data integrity by designing and enforcing rigorous quality control measures at the point of data entry. This includes implementing validation checks, error handling, and monitoring solutions to detect and prevent data anomalies, ensuring that only accurate and complete data is ingested into the systems

Contribute to a culture of continuous learning and improvement by engaging in regular code reviews and peer feedback sessions. Review the work of team members to ensure adherence to best practices, coding standards, and data governance principles, while also offering constructive feedback to help improve the overall quality of the team’s outputs

Qualification

Data Pipeline DevelopmentETL ProcessesAPI DevelopmentCloud TechnologiesCI/CD ToolsData Warehouses/LakesData QualityCollaborationProblem SolvingContinuous Learning