Senior Manager, Data Engineering

Role Description

This is a remote position and can be located anywhere in the US. We are seeking a highly skilled Senior Manager, Data Engineering to design, build, and optimize modern data platforms that power enterprise analytics, reporting, machine learning, and AI initiatives.

• Design and maintain scalable data platforms and pipelines.
• Develop and optimize cloud-based data architectures.
• Automate infrastructure provisioning using Infrastructure-as-Code tools.
• Collaborate with data scientists, analysts, architects, and business leaders to gather requirements.
• Troubleshoot complex technical issues.
• Implement data quality controls and improve platform governance and security.
• Mentor engineers and conduct code reviews.
• Evaluate emerging technologies such as GenAI and machine learning.
• Continuously improve data platform performance, reliability, and cost efficiency across cloud environments including AWS, Snowflake, Azure, and Databricks.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical field.
• Equivalent combination of education and relevant work experience may be considered.
• Master's degree in Computer Science, Information Systems, Data Science, or related field preferred.
• 10+ years of progressive experience in data engineering, analytics engineering, business intelligence, or related technical roles.
• Proven track record designing and delivering enterprise-scale data platforms and analytics solutions.
• Demonstrated ability to lead technical initiatives and influence architectural decisions.
• Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders.
• Experience operating in fast-paced, highly collaborative Agile environments.
• Ability to independently drive projects from concept through implementation and support.
• Strong problem-solving mindset with a focus on business outcomes, automation, and continuous improvement.

Requirements

• Data Engineering & Architecture
• Advanced proficiency in SQL and Python.
• Experience building and maintaining scalable ETL/ELT pipelines.
• Strong expertise in PySpark and distributed data processing.
• Experience designing enterprise data models and lakehouse architectures.
• Deep understanding of data warehousing, data lakes, and modern data platforms.
• Experience implementing data quality, monitoring, and governance frameworks.
• Cloud & Platform Engineering
• Hands-on experience with AWS services such as S3, IAM, Glue, and Lake Formation.
• Experience working with Snowflake, Databricks, Azure, or GCP.
• Experience designing secure, scalable cloud-native data architectures.
• Understanding of cloud security, identity management, and access controls.
• Infrastructure & DevOps
• Experience with Terraform or similar Infrastructure-as-Code tools.
• Strong Git-based development practices.
• Experience implementing CI/CD pipelines and deployment automation.
• Knowledge of platform monitoring, optimization, and operational support.
• Collaboration & Delivery
• Experience partnering with business stakeholders to translate requirements into technical solutions.
• Ability to advise teams on best practices, architecture, and platform capabilities.
• Experience working within Agile, Scrum, Kanban, or SAFe delivery frameworks.
• Strong documentation, communication, and stakeholder management skills.

Benefits

• Medical, Dental, Vision, Health Savings Accounts / Flexible Spending Accounts.
• Life and AD&D Insurance.
• 401(k).
• Tuition Reimbursement.
• Resources that encourage a lifetime of healthier living.
• Compensation ranges from $133,200.00 - $195,000.00 annually, based on skills, experience, and education.