About the company
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr Data Engineer based in United States.
Responsibilities
- Lead finance-focused discovery workshops and revalidation sessions, translating dashboard wireframes and business requirements into measures, dimensions, data grain, date basis, and source requirements.
- Guide the development and validation of AWS Glue and Amazon Redshift data solutions in alignment with finance reporting and analytics requirements.
- Partner with data modelers and engineers to ensure requirements are accurately reflected in conceptual, logical, and physical data models, source-to-target mappings, and curated Redshift layers.
- Work closely with finance functional stakeholders to validate source data, business calculations, reporting logic, and expected results.
- Drive resolution of business definition gaps, source-data questions, offline or manual source dispositions, and cross-functional dependencies.
- Establish and maintain KPI/KSM catalogs, business glossaries, requirements artifacts, validation materials, and stakeholder sign-off documentation.
- Ensure finance stakeholders can effectively validate curated and semantic data layers through clear KPI definitions and structured UAT validation packs.
- Support UAT by explaining expected KPI results and reconciliation outcomes, identifying functional defects, and facilitating timely resolution of finance-related issues.
- Coordinate business sign-offs, key decisions, escalations, RAID management, and change control in collaboration with project leadership.
- Provide finance walkthroughs at the completion of each subject area and support knowledge transfer and handover activities.
- Maintain strong stakeholder engagement and alignment across business, functional, and technical teams throughout concurrent delivery waves.
- Manage competing priorities, dependencies, and sign-off requirements within a parallel, multi-workstream delivery environment.
Requirements
- 10+ years of overall professional experience in data engineering, architecture, or related technology roles.
- 5+ years of hands-on experience with AWS Glue and Amazon Redshift.
- Strong finance domain knowledge covering areas such as Accounts Payable, inventory accounting, COGS/cost accounting, cash management, cash applications, treasury, and bank reconciliation.
- Strong understanding of financial reporting, KPI definitions, reconciliations, accounting periods, control totals, and business validation of finance data.
- Experience leading finance and data discovery workshops and translating business reporting requirements into structured functional and data requirements.
- Experience owning requirements artifacts, KPI/KSM catalogs, business glossaries, sign-off processes, and stakeholder decisions.
- Experience working with data modeling, data warehousing, analytics delivery, and curated or semantic data layers.
- Strong understanding of data reconciliation, UAT, and validation against source-system values and expected business outcomes.
- Ability to collaborate effectively with finance functional consultants, data modelers, data engineers, project managers, and business stakeholders.
- Strong stakeholder management, facilitation, written communication, and executive communication skills.
- Ability to lead across multiple concurrent workstreams, manage competing priorities, and coordinate dependencies and escalations.
- Strong analytical and problem-solving skills, with the ability to bridge complex finance requirements and technical data solutions.
- Ability to work effectively in an onsite stakeholder environment and maintain alignment across business, functional, and technical teams.
Conditions
- $60–$65 per hour.
- Contract engagement running from October 1, 2026 through October 1, 2027.
- Remote contract opportunity with an onsite lead/stakeholder engagement component.
- Opportunity to lead finance-focused data transformation and analytics initiatives.
- Exposure to AWS Glue, Amazon Redshift, financial data modeling, and enterprise reporting.
- Collaboration with finance, data engineering, architecture, and project leadership teams.
- Opportunity to influence data quality, KPI governance, reconciliation, and business validation processes.