Data Engineer / Architect III - Finance Domain

Position Summary

Seeking a Data Engineer / Architect III to support a large-scale Merger & Acquisition (M&A) initiative within a complex financial services environment. This role focuses on enterprise data architecture, cloud data engineering, scalable ELT/ETL pipelines, and regulatory-grade data integration. The ideal candidate will possess strong expertise in Snowflake, DBT, Advanced SQL, Data Warehousing, and Enterprise Data Modeling.

This is a highly visible role requiring both hands-on engineering execution and architectural leadership while partnering with business stakeholders, enterprise architects, analysts, and reporting teams.

Employment Type : W2 – Full Time

Location : Cincinnati, Ohio (Onsite)

Industry : Financial Services / Banking

Contract Type : Long-Term Contract

Submission Deadline :June 2, 2026

Required Skills

• Snowflake

• DBT

• Advanced SQL

• Data Warehousing

• ELT / ETL Engineering

• Enterprise Data Modeling

• Data Architecture

• Cloud Data Platforms

• Data Integration

• Data Transformation Frameworks

Preferred Skills

• Financial Services / Banking Experience

• Regulatory Reporting

• Power BI

• Data Governance

• M&A Integration Projects

• Java / J2EE

• Backend Engineering Experience

Key Responsibilities

Enterprise Data Engineering & Architecture

• Design and implement scalable enterprise data architectures.

• Build and optimize cloud-native ELT/ETL pipelines using Snowflake and DBT.

• Develop reusable transformation frameworks and enterprise data models.

• Design scalable solutions supporting analytics, reporting, and operational data needs.

• Create high-performance analytical and operational data structures.

M&A Data Integration

• Support enterprise merger and acquisition data integration initiatives.

• Analyze and consolidate disparate data sources from acquired organizations.

• Standardize enterprise data definitions, mappings, and transformation logic.

• Ensure accurate migration and reconciliation of financial and operational data.

• Support enterprise-wide data consolidation efforts.

Data Quality & Governance

• Implement data validation and reconciliation processes.

• Support:

  • Data Lineage

  • Governance

  • Auditability

  • Regulatory Reporting Requirements

• Improve platform reliability, scalability, and maintainability.

• Assist with disaster recovery and operational resiliency planning.

Leadership & Collaboration

• Partner with:

  • Enterprise Architects

  • Data Engineers

  • Business Analysts

  • Reporting Teams

  • Data Scientists

  • Business Stakeholders

• Translate business requirements into scalable technical solutions.

• Participate in:

  • Architecture Reviews

  • Agile Ceremonies

  • Technical Planning Sessions

• Evaluate emerging technologies and engineering best practices.

Technical Environment

Cloud Data Platform

• Snowflake

Data Transformation

• DBT

• ELT / ETL Frameworks

Databases

• Relational Databases

• Non-Relational Databases

Analytics & Reporting

• SQL

• Power BI (Preferred)

Architecture

• Enterprise Data Modeling

• Data Warehousing

• Data Governance

Additional Technologies

• Java / J2EE (Preferred)
  

What Success Looks Like

• Deliver scalable and reliable enterprise data solutions.

• Successfully integrate data across M&A initiatives.

• Build optimized Snowflake and DBT transformation frameworks.

• Improve enterprise reporting, analytics, and governance capabilities.

• Ensure regulatory-quality data management and operational excellence.