Data Engineering Manager (Remote - US)

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.

• Competitive base salary: $159,000–$212,000 annually, based on experience and skills.
• Company equity through stock options and performance-based bonuses.
• Employer-paid health, vision, and dental insurance coverage.
• Flexible vacation and remote work arrangements.
• Paid parental leave and team-building events.
• Educational assistance and free gym membership.
• Casual dress code and a collaborative, mission-driven work environment.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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