Find & Apply For Database Architect Jobs in Clearwater, Florida

Job Description Help for Job Description. Opens a new window. Must have the following in order to apply: Ten (10) years of experience across data engineering, enterprise data platforms, data architecture, financial data systems, or related disciplines Three (3)+ years of experience leading data engineering, data platform, or financial data teams

Preferred Qualifications:

Experience building, leading, or modernizing a Finance Data Platform, Finance Data Mart, Finance Data Warehouse, or comparable financial data ecosystem Experience migrating legacy SQL Server, SSIS, ADF, stored procedure, or traditional data warehouse workloads to Databricks or another cloud-native platform Experience with commission and incentive compensation platforms such as Varicent or comparable technologies Experience with financial planning, consolidation, and performance management platforms such as OneStream or similar solutions Experience within insurance, financial services, distribution, commissions, or other transaction-intensive industries Experience working with master and reference data involving companies, legal entities, carriers, products, producers, policies, contracts, accounts, and organizational hierarchies Familiarity with Data Vault 2.0, dimensional modeling, medallion architecture, Unity Catalog, data lineage, and modern data governance practices Experience managing blended teams consisting of employees, contractors, and strategic delivery partners Databricks certification and/or relevant Azure or AWS certifications preferred

Skills:

Demonstrated experience designing, building, or operating large-scale enterprise data platforms supporting business-critical workloads Hands-on experience with Databricks, Apache Spark, Delta Lake, or comparable modern cloud data technologies Advanced SQL skills with strong knowledge of data engineering, ETL/ELT, integration, pipeline design, and performance optimization Experience with cloud platforms such as Azure or AWS Understanding of financial data and processes, including multiple areas such as P&L, FP&A, General Ledger, commissions, banking, journal entries, financial reporting, reconciliation, allocations, attribution, planning, and forecasting Experience supporting data environments where accuracy, auditability, lineage, reconciliation, and financial controls are critical Knowledge of enterprise data modeling, dimensional modeling, and modern lakehouse architectures Experience managing production data workloads and resolving complex data, pipeline, reconciliation, and platform issues Experience implementing automated testing, monitoring, data quality, CI/CD, and production controls Demonstrated ability to translate complex Finance requirements into scalable data solutions Proven ability to lead teams operating across strategic initiatives, rapid enhancements, and business-critical production responsibilities Communication and stakeholder-management skills with the ability to partner effectively with Finance and senior technology leaders Mindset of a Finance data leader, hands-on data engineer, and platform operator Comfortable discussing a P&L or commission reconciliation with Finance, reviewing SQL and pipeline logic with an engineer, diagnosing a production data issue, challenging a data model, and defining the roadmap for modernizing FDM capabilities on Databricks Success in this role requires technical judgment, financial data fluency, operational discipline, and the ability to bring structure to a fast-moving environment without introducing unnecessary bureaucracy Will be expected to make the Finance Data Platform increasingly scalable, automated, governed, and reliable while preserving the responsiveness Finance requires from a mission-critical data function

Required Screenings:

Employer will discuss.

Job Description:

Seeking a Senior Manager, Finance Data Platform to lead the engineering, delivery, operations, and modernization of our enterprise finance data ecosystem. Reporting directly to the Vice President of Enterprise Data & AI Platforms, this leader will have responsibility for the Finance Data Platform (FDM) and the broader data capabilities supporting Finance, Accounting, FP&A, Commissions, Banking, General Ledger, financial reporting, attribution, reconciliation, and related financial processes. This is a hands-on technology leadership role requiring a combination of enterprise data platform experience, financial data domain knowledge, engineering depth, and people leadership. The Senior Manager will lead a team of engineers and finance data specialists while working closely with Finance stakeholders to translate complex financial requirements into reliable, scalable, and well-governed data solutions. A key mandate for this role will be evolving existing FDM capabilities into a modern, enterprise-grade Finance Data Platform built on Databricks, while maintaining the responsiveness required to support fast-moving Finance priorities and business-critical operations.

Key Responsibilities:

Finance Data Platform Leadership Lead the engineering, delivery, operations, and ongoing evolution of the Finance Data Platform Provide day-to-day leadership for engineers, finance data specialists, and partner resources supporting FDM and related finance data capabilities Establish clear priorities across Finance enhancements, strategic initiatives, production issues, reconciliations, data quality, technical debt, and platform modernization Build an operating model that supports rapid Finance-driven changes while maintaining engineering discipline, reliability, governance, and appropriate controls Partner closely with Finance, Accounting, FP&A, Commissions, Data Architecture, Data Engineering, and enterprise technology teams Translate complex Finance requirements and business rules into scalable technical solutions and executable engineering priorities Establish clear accountability across engineering, functional expertise, QA, delivery, and operational support Finance & FDM Domain Develop deep expertise in the existing FDM ecosystem, including its business processes, data models, transformations, integrations, dependencies, and downstream consumers Lead data capabilities supporting: Partner with Finance stakeholders to understand calculation logic, mappings, hierarchies, allocations, attribution rules, reconciliation requirements, and reporting dependencies Ensure financial data can be traced and reconciled from source systems through transformation and downstream consumption Support integrations with financial planning, commission, accounting, reporting, and enterprise performance management platforms Databricks & Enterprise Data Engineering Lead the modernization and migration of Finance data capabilities onto the enterprise Databricks Lakehouse platform Design and oversee scalable ingestion, transformation, integration, and publishing patterns for complex financial datasets Apply modern lakehouse and medallion architecture principles across Bronze, Silver, and Gold layers Drive engineering standards including reusable frameworks, metadata-driven pipelines, automated testing, CI/CD, observability, and infrastructure automation Work across databases, APIs, files, SFTP feeds, enterprise applications, and other structured and semi-structured data sources Optimize Databricks workloads for performance, scalability, reliability, and cost Maintain SQL and data engineering standards across the team Partner with enterprise Data Architecture and Engineering leadership on data models, integration patterns, architecture standards, and platform strategy Drive the progressive retirement and simplification of legacy FDM components as capabilities transition to the enterprise data platform Financial Data Modeling, Quality & Controls Ensure data models appropriately represent financial transactions, accounts, entities, products, carriers, producers, policies, contracts, commissions, and organizational hierarchies Establish reconciliation capabilities across source systems, FDM, Databricks, General Ledger, financial applications, and downstream reporting Ensure appropriate historical tracking, auditability, lineage, and point-in-time analysis for critical financial data Partner with Data Architecture and Governance teams to establish consistent business definitions, metadata, lineage, ownership, and data quality standards Establish automated controls for completeness, accuracy, timeliness, duplication, referential integrity, and financial reconciliation Ensure appropriate security and access controls for sensitive financial information Drive root-cause analysis and permanent remediation of recurring data quality and reconciliation issues Delivery & Operational Excellence Lead execution across Finance data projects, enhancements, defects, operational requests, and production issues Establish a delivery model capable of supporting fast-paced Finance requirements that may not always align to traditional sprint-based development cycles Create clear processes for distinguishing and managing enhancements, strategic projects, production incidents, defects, and recurring operational activities Balance immediate Finance priorities with long-term platform modernization and technical sustainability Establish service expectations, prioritization mechanisms, escalation paths, and measurable delivery outcomes Reduce manual processing and operational dependencies through automation and engineering improvements Establish monitoring, alerting, incident management, and production-readiness practices for critical Finance data pipelines Coordinate internal teams and external delivery partners while maintaining clear internal accountability for outcomes People Leadership Lead, mentor, and develop a high-performing Finance Data Platform team Build a team with the right combination of data engineering, financial domain, functional, and operational expertise Develop team members' understanding of both the technology and the financial processes supported by the platform Create clear ownership and accountability while enabling engineers and specialists to operate with appropriate autonomy Manage internal employees, contractors, and strategic delivery partners Participate in hiring, workforce planning, performance management, and capability development as the Finance Data Platform organization evolves

Work Environment:

Will be discussed with applicant.

Hiring Process:

Submit resume via email. In order to apply to this position, please click "Apply" located at the top of the job order page, and you will receive the employer contact information. Employer has indicated the means listed are the only means they will accept to apply.

Days & Hours:

Full Time position. Complete work schedule will be discussed with applicant.

Pay:

$150,000 per year; depends on experience. Annual bonus. Benefits are offered.