Manager Data Engineering

We are seeking a Manager-Level Data Architect to lead and support a team of data engineers while driving the evolution of our enterprise data platform. This role combines deep technical expertise in SQL Server database administration with modern data engineering practices, and plays a key role in our transition from self-managed IaaS-based database platforms to fully managed PaaS solutions.

The ideal candidate brings strong hands-on DBA experience, proven leadership of small engineering teams, and a track record of planning and executing database migrations to cloud-managed services. This individual will partner closely with Program Management (PM) to ensure effective planning, execution, and delivery of data platform initiatives.

Responsibilities:

Leadership & Delivery

• Lead, mentor, and manage a team of 3-5 data engineers across platform and integration tracks
• Collaborate with Program Managers to plan, prioritize, and execute data initiatives
• Drive accountability for project delivery, operational excellence, and continuous improvement
• Provide technical guidance and architectural oversight across all data-related workstreams

Data Platform Engineering

• Oversee setup, configuration, and maintenance of data platforms and environments

• SQL Server clusters (IaaS, self-managed)
• Aurora PostgreSQL and other cloud-native databases
• BI platforms (SSRS, Tableau, PowerBI)

Lead database administration activities including performance tuning, high availability, backup/recovery, and upgrades

Define and implement access control, governance, and security best practices

Drive DataOps practices including monitoring, reliability, and performance optimization

Implement and manage CI/CD pipelines for database and platform deployments (Python, Liquibase)

Lead security remediation efforts and compliance initiatives

Data Integration Engineering

• Oversee design and development of scalable data pipelines and integration workflows
• Guide implementation of ETL/ELT processes using SSIS, AWS Glue, and Python
• Support development and optimization of data marts and analytical data models
• Ensure strong DataOps practices including data quality, observability, and freshness monitoring
• Lead and support data migration efforts, particularly SQL Server to PaaS transitions
• Optimize performance and scalability of data pipelines and integration processes

Cloud Migration & Modernization

• Plan and execute migration strategies from SQL Server (IaaS) to managed PaaS database services
• Evaluate target architectures and recommend best-fit cloud-native solutions
• Ensure minimal disruption and high data integrity during migration processes

• 10+ years of experience in data architecture, database administration, or data engineering roles
• Strong hands-on experience as a SQL Server DBA (current or prior role), including performance tuning, HA/DR, and operational support
• Proven experience leading small engineering teams (5-7 members)
• Experience designing and managing self-hosted database environments (IaaS)
• Demonstrated experience planning and executing database migrations to PaaS/cloud-managed services
• Strong understanding of DataOps practices, including monitoring, reliability, and performance management
• Experience building and maintaining data pipelines and ETL/ELT processes (SSIS, Glue, Python)
• Experience with CI/CD tools and practices for data platforms (e.g., Liquibase, Python-based automation)
• Familiarity with BI tools such as SSRS and Tableau
• Strong collaboration skills and experience working closely with Program/Product Management
• Solid understanding of data security, governance, and access control

Preferred Qualifications:

• Experience with AWS data services (e.g., Aurora PostgreSQL, Glue, S3, RDS) or equivalent cloud platforms
• Experience with PostgreSQL or other open-source databases
• Familiarity with stream processing technologies (e.g., Apache Flink)
• Knowledge of infrastructure-as-code and automation tools (e.g., Terraform, CloudFormation)
• Experience implementing enterprise-grade data observability and data quality frameworks
• Background in supporting large-scale, highly available production data systems
• Strong communication skills with the ability to translate technical concepts for non-technical stakeholders

• Competitive compensation and benefits package.
• Flexibility to support work-life balance.
• Comprehensive health benefits for you and your family.
• Generous paid leave and holidays.
• Wellness program and employee assistance.

Pay Range: $140,000-$190,000