Manager, Data Engineering

Title: Manager, Data Engineer 

Role Description: 

ShipBob views Data Engineering as a true Center of Excellence across our platform and organization. The Manager, Data Engineering will play a critical leadership role in executing this vision by leading a team of Data Engineers responsible for building, maintaining, and scaling enterprise-grade data systems.  

This role is accountable for the end-to-end execution of data engineering initiatives, including data ingestion, transformation, storage, reliability, and platform scalability. The Manager will oversee the development and maintenance of our modern cloud-based data platform built on Azure technologies (including ADLS and Databricks), ensuring high standards for data quality, governance, availability, and performance.  

The Manager, Data Engineering will partner closely with Analytics Engineering, Finance, Product, Operations, and Engineering stakeholders to deliver reliable, scalable, and well-governed data solutions that power reporting, business intelligence, machine learning, and AI initiatives.  

This is a people leadership role managing individual contributors. The ideal candidate brings strong technical depth, a passion for operational excellence, and a proven ability to build high-performing teams in fast-paced environments.  This role reports to Sr. Director, Engineering.

What you’ll do: 

• Manage and Develop a High-Performing Team: Hire, mentor, and manage a team of Data Engineers. Provide clear goals, career development guidance, and ongoing performance feedback. Foster accountability, ownership, and engineering excellence.  
• Own Data Engineering Execution: Oversee the design, development, and operation of scalable data pipelines and platform capabilities across our cloud data environment. Ensure reliable ingestion, transformation, and availability of structured and unstructured data.  
• Enforce Platform Best Practices: Implement and enforce industry best practices for data modeling, pipeline orchestration, testing, monitoring, observability, and cost efficiency across Azure-based data infrastructure (ADLS, Databricks, and related tooling).  
• Operational Excellence & Reliability: Define and manage SLAs for production data processes. Ensure high standards for data quality, reliability, and performance. Proactively identify risks and engineering bottlenecks before they impact the business.  
• Collaborate Cross-Functionally: Partner with Analytics Engineering and business stakeholders (Finance, Operations, Product, Revenue) to translate business requirements into scalable technical solutions. Ensure alignment between engineering execution and business priorities.  
• Support Governance & Compliance: Operationalize data governance, data protection, and compliance frameworks (including GDPR and other global requirements) in partnership with leadership. Ensure secure and responsible data management practices.  
• Enable BI and AI/ML Capabilities: Ensure the data platform effectively supports analytics, reporting, machine learning, and AI workloads through well-structured, discoverable, and trusted datasets.  
• Elevate Organizational Maturity: Improve engineering processes, documentation standards, code review rigor, deployment practices, and cross-team coordination to elevate the overall maturity of the Data Engineering function.  
• Partner in Planning & Roadmapping: Collaborate with the Director of Data Engineering on roadmap planning, resource allocation, and prioritization to ensure successful execution of strategic initiatives.  
• This role requires working overlapping hours with U.S.-based colleagues, including evening or overnight hours in India aligned to Central Standard Time (CST). 
• Additional duties and responsibilities as necessary. 

What you’ll bring to the table: 

• 8+ years of experience in Data Engineering or related technical fields.  
• 3+ years of experience managing and developing individual contributor engineering teams.  
• Established experience building and maintaining modern cloud-based data platforms (data lakes, lakehouse, or data warehouse architectures).  
• Solid hands-on expertise in data pipeline development, SQL, distributed data processing, and cloud-native data services.  
• Experience working with Azure-based data ecosystems (e.g., ADLS, Databricks) or similar modern cloud data platforms.  
• Demonstrated ability to implement data governance, quality, and observability best practices.  
• Experience supporting BI, analytics, and machine learning workloads at scale.  
• Sound understanding of data modeling, ingestion frameworks, and data transformation strategies.  
• Experience collaborating across distributed teams and cross-functional stakeholders.  
• Excellent communication and stakeholder management skills.  
• Demonstrated success hiring, mentoring, and scaling engineering talent.  
• Ability to balance hands-on technical guidance with people leadership responsibilities.  
• Familiarity with global data protection and compliance requirements (e.g., GDPR, SOC-2) preferred.  
• Bachelor’s degree in Computer Science, Engineering, or a related technical field preferred. 

Perks & Benefits: 

• Medical, Term & Accidental Insurance 
• All Purpose Leave (casual & sick time): 12 days 
• Earned Leave: 15 days 
• Public Holiday: 12 days 
• Generous Maternity & Paternity Leave 
• Quarterly Wellness Day 
• Work From Home Allowance 
• See Our High-Performing Culture >>> Check us out on Instagram (@lifeatshipbob)