Data Engineering Manager (Cloud Services and Data Transformation)

Data Engineering Manager

Overseeing and driving the success of data engineering workgroups, combining technical expertise with people management skills; drives the analysis, design, development, test, deploy and optimization of data infrastructure and pipelines to support critical data initiatives across the organization to support our ministries' needs. Requires a highly skilled and experienced technical leader responsible for managing, mentoring, guiding and empowering their workgroups in successful delivery of data-driven projects, ensuring best practices in development, automation and security are followed while fostering a culture of innovation and continuous improvement.

An HR Leader, reports to Delivery Leader. Takes full ownership of technical project oversight, driving the delivery roadmap for aligned product(s) / and service(s) across multiple workgroups; ensures all technical requirements are met and development is completed according to requirements. Reviews estimations and story points, challenging them when necessary to ensure realistic timelines and resource allocation. Drives data analysis, data pipeline design, automation, code quality, security standards and compliance of data products & services. Owns and removes technical dependencies that may impede workgroup's progress, fostering a culture of continuous improvement. Keeps the team focused on delivering work items within the data pipeline lifecycle, fulfilling iteration goals and commitments defined in the product version. Ensures the testing strategy is developed and completed successfully, including Test Plans, Test Cases, Test Scripts, Functional Testing, and documentation of testing outcomes, approving communication for UAT readiness. Validates successful completion of unit, integration, functional, pre UAT (if applicable), UAT & and performance testing. Ensures all delivery steps in the SDLC have been performed (analysis, design, build, testing, issue resolution) to enable product deliverable signoff and release scheduling. Reviews and approves iteration progress metrics within Jira and status reporting, driving delivery roadmap alignment to product and program roadmaps. Drives handoff of data product / service deliverables to DataOps, ensuring quality knowledge transfer and validates acceptance. Collaborates across diverse functional groups to drive consensus across project delivery. Collaborates, Drives & Liaisons across Delivery workgroups to ensure overall delivery of the Data product / Service or the overall Program. Provides clear and concise updates to the PMO or P&E Specialist on the status of key data engineering projects, ensuring transparency and effective communication across teams and stakeholders. Participate in Sprint Ceremonies to ensure alignment on deliverables planned, identify potential issues, risk & drive resolution working with required teams. Collaborate with Release & Change Management lead for Release Planning & Operationalization. Facilitates communication, empowers workgroups to self-optimize their processes, ensures workgroups have necessary resources, and removes any impediments to the team (issue & conflict resolution) in a timely manner. Collaborate with MSP's / Augmentation partners to ensure their deliverables are meeting the workgroup needs. Drives associate growth via HR duties - 1 : 1s, Quarterly Syncs, Performance Reviews, Training Support.

Strong technical proficiency in data engineering technologies (eg ETL tools, Spark, Kafka, DataForm), cloud data platforms, preferably GCP (others include Azure, AWS), data pipeline orchestration (eg Apache, Airflow, Jenkins), and extracts. Expertise in programming languages such as Python, Java, Scala. Master Data Management experience is a plus, but not required. In-depth knowledge of database management (SQL, NoSQL), data warehousing, data lake, and data integration solutions. Adept at facilitating critical technical decisions, aligning teams around pipeline architecture and execution. Strong understanding of data architecture principles, including scalability, reliability and security. Proven ability to lead and mentor technical teams with experience in conflict resolution, collaboration, and fostering a culture of learning, accountability, and high performance. Ability to analyze complex technical problems and develop innovative solutions to overcome challenges. Open to learning and adapting new technologies, tools, and methodologies to keep the team competitive in a rapidly evolving field. Understanding of modern database solutions like Graph DB, Vector DB, Salesforce Cloud, AI technologies, with ability to translate to consumer needs & dependencies tracking. Comfortable challenging the existing ways of working with Product Owners, Architects, Test Leads, and Tech Leads to improve processes and outcomes. Strong willingness to challenge existing processes and advocate for new approaches that increase efficiency and quality. Proven track record of meeting deadlines, adjusting to scope changes, and adapting plans as necessary to align with organizational priorities. Bachelor's degree preferred : At least 5-7 years of experience in data engineering or a related field, with at least 2-3 years in a leadership role.