ShipBob

Manager, Data Engineering

Rol remoto de Data Engineering Manager con fit claro de ubicación del candidato.

Publicado2 jul 2026

Países elegibles40 países aceptados

Señal de seniorityLead

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

AlbaniaAustriaBielorrusiaBélgicaBulgariaCroacia+34 más

Azure SQL

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Actualidad de la fuente2 jul 2026

Fit de ubicación40 países aceptados

Match de stackAzure, SQL

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Aplicando aManager, Data EngineeringShipBob

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Resumen del rol

Manager, Data Engineering

Requisitos y responsabilidades

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Details

Grow with an Ownership Mindset: We champion continuous learning and innovation. You'll take on real problems, create tangible solutions, and drive results that move the needle for ShipBob, our merchants, and for your own professional growth. If you're ready to do the most meaningful work of your career, this is the place.
Collaborate with Peers and Leaders Alike: At ShipBob, leaders are accessible; feedback flows in both directions, and everyone, regardless of their seniority or role, steps up to help when needed. We hold each other to high standards because we trust each other to meet them. That combination of transparency and mutual respect is what makes the work here feel worth doing.
Experience a High-Performance Culture and Clear Purpose: We are results-driven and clear about what that means: our goals are specific, accountability is shared, and every team member can see how their work connects to our mission. When we hit milestones, we celebrate them together. When we fall short, we learn and move forward.

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.