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Data Engineering Manager (Remote - US) at Jobgether. This position is posted by Jobgether on behalf of Self Financial, Inc. We are currently looking for a Data Engineering Manager in United States.. As a Data Engineering Manager, you will lead a high-performing team responsible for building trusted, scalable, and well-governed data systems. You will drive the modernization of data pipelines, improve quality and observability, and optimize data transformations to support product growth and strategic decision-making. Partnering closely with cross-functional teams, you will ensure that critical metrics, analytics, and insights are delivered reliably and efficiently. This role thrives in a fast-paced, mission-driven environment where collaboration, innovation, and continuous improvement are essential. Your leadership will directly influence the accuracy, accessibility, and impact of data that powers key business initiatives and customer outcomes.. . Accountabilities. . Lead, coach, and grow a team of data engineers, setting clear goals, feedback loops, and development plans.. . Modernize ETL/ELT pipelines, standardize orchestration, and retire legacy systems to improve reliability and maintainability.. . Design and maintain robust data models, ensuring performance, scalability, and incremental processing.. . Implement data quality monitoring, anomaly detection, and observability practices, including SLAs/SLOs for freshness, availability, and accuracy.. . Establish data lineage, cataloging, governance, access controls, and compliance measures for sensitive information.. . Optimize cost and performance for data workloads, storage, and queries while maintaining high reliability.. . Partner with analytics, product, ML, fraud, and accounting teams to translate business needs into a clear data roadmap.. . Track and report on team OKRs and metrics, including pipeline success rate, MTTR/MTTD, and stakeholder satisfaction.. . . . 6+ years of experience in data engineering or a closely related field, with at least 2 years in a leadership or management role.. . Expert-level SQL and strong proficiency in Python.. . Hands-on experience designing, building, and operating ETL/ELT pipelines and orchestration frameworks (e.g., Airflow).. . Experience with cloud data warehouses such as Redshift, BigQuery, or Snowflake, and transformation frameworks like dbt.. . Solid understanding of data modeling, performance tuning, and pipeline optimization.. . Proven experience implementing data quality, observability, and lineage processes; able to manage on-call and incident response.. . Strong stakeholder management, communication, and problem-solving skills, with the ability to translate ambiguous business requirements into actionable data strategies.. . Familiarity with security, privacy, and governance best practices in data systems.. . Company Location: United States.