Data Engineering and Delivery Manager

About this role

About The Lisinski Law Firm

Since 2020, Lisinski Law Firm has served as a dedicated humanitarian immigration practice committed to providing meaningful support to individuals and families seeking safety, stability, and a path forward. We frequently stand with clients who have been turned away elsewhere, offering both advocacy and care. Joining our Firm means becoming part of a team devoted to keeping families together and “Changing as Many Lives as Possible.”

About the Role

The Data Engineering and Delivery Manager leads and develops the Data Engineering team to deliver reliable, secure, and scalable data solutions that support the Firm’s operational and strategic goals. This role oversees the performance of the Firm’s data platform and the delivery of engineering initiatives, ensuring alignment with established technical standards and data governance requirements. In partnership with the Director and Business Intelligence Manager, this position manages a centralized intake process and prioritized backlog across Business Intelligence and Data Engineering, balancing business needs, team capacity, and delivery timelines. The Manager drives effective Agile practices, coordinates work across teams and removes barriers to ensure efficient and accountable delivery. Serving as a primary point of contact for business stakeholders, this role communicates priorities, progress, and risks while continuously improving processes to strengthen collaboration and deliver measurable business value.

Your Key Contributions

• Manage and develop the Data Engineering team across multiple countries and time zones, overseeing hiring, onboarding, coaching, performance management, development plans, and workload.

• Own delivery of the Data Engineering roadmap, including the Microsoft Fabric warehouse migration, the CI/CD program with the Firm’s consulting partner, and data readiness for the Salesforce Revenue Cloud go-live.

• Oversee the reliability, availability, security, and cost of the Firm’s data pipelines and warehouse; maintain documented ownership for every production feed and pipeline and assign cross-training to prevent reliance on a single team member.

• Partner with the Data Governance Platform Architect and Business Intelligence Manager to apply consistent engineering standards, source control, deployment practices, and governance; ensure compliance with the Firm’s data handling, security, and regulatory obligations, limiting documented work-item risks to delivery and data handling.

• Manage a centralized intake process for reporting and data requests from all departments, requiring a requester, business owner, purpose, and acceptance criteria before work begins; establish and enforce Definitions of Ready and Done that address each Feature’s scope, risks, mitigation plans, and success measures.

• Maintain a single prioritized backlog for Business Intelligence and Data Engineering with the Director and Business Intelligence Manager, making and communicating trade-off decisions while reserving approximately 15% of capacity for defects and technical debt.

• Own handoffs between Business Intelligence and Data Engineering, ensuring named owners and visible status prevent requests from falling between team boards; serve as the primary stakeholder contact and publish delivery status, cycle times, and request queues on a fixed schedule.

• Facilitate Sprint Planning, Backlog Refinement, Sprint Reviews, and Retrospectives for both teams, supporting daily stand-ups until teams can run them independently; remove impediments and escalate blocks exceeding five business days or urgent requests that challenge reserved capacity to the Director.

• Maintain Azure DevOps configuration, templates, and the team wiki in alignment with the operating model, partnering with team engineers to implement changes; track and publish board health measures covering descriptions and acceptance criteria, skipped Active status, items stranded in completed sprints, cycle time by work category, and the proportion of unplanned work delivered.

• Represent the data function in enterprise project routing and alignment meetings with EPMO, IT, and Product to communicate intake requirements and capacity before staffing decisions; report priorities, progress, risks, capacity, cycle time, defect rate, queue length, and declined requests to the Director in clear terms.

What Makes You a Great Fit

• Decision Quality: Balances technical recommendations, business priorities, capacity and delivery timelines; decides which requests are worked, in what order, and says so in writing with the reason.

• Directs Work: Sets clear priorities, assigns work, manages team capacity, holds team members accountable for results, and adapts the plan when the business changes.

• Builds Effective Teams: Recruits, develops, coaches and retains a distributed engineering team; sets expectations, gives regular feedback, and creates a collaborative, inclusive environment.

• Collaborates: Builds working partnerships with the Business Intelligence team, IT, the Product organization, the EPMO, Operations, Finance, Marketing and Legal; treats the requester as a partner, not a ticket.

• Instills Trust: Meets commitments, gives transparent status including bad news, and makes the queue visible so stakeholders stop routing around it.

• Working knowledge of Microsoft Fabric, Azure SQL, Azure Data Factory, Python, SQL, REST APIs, source control and CI/CD, and modern data warehouse and ELT practice, sufficient to guide decisions and review plans.

• Hands-on Agile delivery experience: facilitating ceremonies, running a backlog, using Azure DevOps or Jira to manage sprints, flow metrics and boards. Familiarity with Scrum and Kanban; Scrumban in practice.

• Ability to write a clear user story, acceptance criteria and a one-page status update.

Minimum Education and Experience Requirements

• Bachelor’s degree in Information Systems, Computer Science, Business, or…