Vice President of Engineering, Data

Convera is a leading B2B cross-border payments company. Our data sits across a legacy platform, an operational data store, and a long tail of source systems. Bringing it into a single governed store is one of the central commitments in our go-forward plan - it is what reporting, analytics, and effectively every AI initiative in the company are currently waiting on.

This role owns Data Engineering, Solution Data Architecture, and Data Science, and is accountable for delivering Convera's enterprise data platform while ensuring continuity of existing operational and regulatory workloads throughout the transformation.Your responsible for modernizing the enterprise data estate by progressively migrating legacy reporting platforms (including DataHub and, over time, ODS) to the Convera Enterprise Data Platform (CEDP), enabling trusted reporting, analytics, AI and regulatory capabilities on a unified foundation. Your first job is to take hold of an in-flight transformation without dropping it. Your second is to finish it, leaving behind a data estate that stands up to regulators, auditors and supports enterprise AI.

• Deliver the single data store. Consolidate Convera's data into one governed platform that reporting, analytics, and AI enablement all build on. The target platform has been selected; your job is execution, not another evaluation cycle. • Lead the phased migration from legacy reporting platforms to the enterprise data platform while maintaining uninterrupted business and regulatory operations. • Hold the committed roadmap. Take over an in-flight program with milestones already communicated. Continuity comes first - sustain delivery, then raise the bar. Renegotiating the plan is an option of last resort, and you will be expected to say so early if it becomes one. • Run the ODS and decide its future. Keep the operational data store stable and feeding transactional systems throughout the migration - this is a run responsibility, not a legacy footnote - and make and defend the call on what happens to it when the target platform lands. • Partner with Enterprise Architecture on enterprise-wide data standards, canonical models, reference architecture, information models and technology strategy. Clearly define operating boundaries between Enterprise Data Architecture and Solution Data Architecture. • Build the pipelines. ETL and ELT at scale out of a complex legacy estate, including streaming pipelines for real-time data movement, with reconciliation to source, monitoring, and recovery that hold up under scrutiny. Data movement that fails quietly is worse than data movement that fails loudly. • Own data science. Set direction for analytical and machine learning work that changes decisions - pricing and margin, risk, client behavior - and partner with Risk and Compliance on model governance so what you build is defensible as well as accurate. • Own governance, quality, and stewardship. Definitions, lineage, ownership, and quality service levels that the business trusts because they match what it experiences. Governance is something people run, not something they read. Establish clear ownership, lineage, definitions and quality standards that the business trusts and actively uses. Partner to ensure that governance accelerates delivery, not become administrative overhead. • Protect the data by design. Secure storage, encryption, masking and tokenization, access control, and retention across every jurisdiction we operate in - built into the platform rather than bolted on when someone asks. • Stand in front of regulators and auditors. Convera is regulated in multiple markets. You will be the person who explains the data estate to an examiner or an auditor, and who stands behind the answer. • Serve the rest of the business. Dashboards and reporting sit elsewhere today; collaborate with the