Senior Data Engineer (Hybrid)

Senior Data Engineer to support a large-scale enterprise data modernization initiative focused on migrating critical banking and enterprise data assets into a centralized Snowflake platform. This strategic program will transform how data is organized, governed, and utilized across the organization, enabling improved analytics, reporting, data quality, and business decision-making. The consultant will join a multi-year transformation effort focused on migrating approximately 30 enterprise data domains from legacy platforms into a modern cloud-based ecosystem. Working within an Agile environment, this individual will play a critical role in designing, engineering, testing, governing, and supporting enterprise data solutions that power the future state of data and analytics across the organization., * Data Migration & Modernization

• Analyze source systems, legacy databases, and existing data architectures.
• Design and implement Snowflake database structures, schemas, and data models.
• Migrate enterprise data assets from multiple source systems into Snowflake.
• Build, enhance, and maintain ETL/ELT processes utilizing SSIS and related technologies.
• Develop data transformation logic to support reporting and analytics requirements.
• Validate data integrations and transformation accuracy.

• Data Engineering

• Design, develop, and maintain scalable data pipelines.
• Optimize data ingestion, transformation, and storage processes.
• Support Azure DevOps (ADO) CI/CD pipelines and deployment automation.
• Create reusable frameworks, standards, and methodologies for data movement and integration.
• Develop SQL and Python-based solutions to support enterprise data initiatives.

• Reporting & Analytics

• Develop reporting datasets and data marts.
• Support the creation of business intelligence and analytical solutions.
• Ensure consistency and accuracy between reports and source systems.
• Collaborate with business stakeholders to support reporting requirements.

• Data Governance & Data Quality

• Support enterprise data governance initiatives and best practices.
• Implement and maintain data retention policies.
• Improve data quality, consistency, lineage, and integrity.
• Assist with metadata management and governance programs.
• Support evaluation and implementation of governance platforms such as Microsoft Purview.
• Contribute to Master Data Management (MDM) initiatives.

• Quality Assurance & Testing

• Develop data testing strategies and quality assurance processes.
• Support reconciliation, data validation, and defect remediation activities.
• Participate in User Acceptance Testing (UAT) and QA cycles.
• Support deployment validation and production release activities.

• Operational Support

• Provide ongoing support for production data platforms and related processes.
• Troubleshoot performance issues, data failures, and platform incidents.
• Perform root cause analysis and implement corrective actions.
• Support quarterly release cycles and post-deployment activities.
• Assist with future migration and platform enhancement initiatives.

• Documentation & Knowledge Transfer

• Create and maintain technical documentation, including:
• Data mappings
• Source-to-target specifications
• ETL/ELT process documentation
• Data lineage documentation
• Architecture diagrams
• Operational procedures
• Conduct knowledge transfer sessions with internal teams.
• Promote engineering standards, documentation practices, and best practices., Required/Desired Amount of Experience Experience in Data Engineering, Data Warehousing, or Data Management. Required 7 Years Strong experience designing and developing solutions within Snowflake. Required Years Advanced SQL development skills. Required Years Experience with SSIS and enterprise ETL development. Required Years Experience building ELT/ETL pipelines and data integration solutions. Required Years Experience with Azure DevOps (ADO), CI/CD pipelines, and release management. Required Years Experience with data modeling, schema design, and database architecture. Required Years Knowledge of data governance, metadata management, and data quality frameworks. Required Years Experience supporting Agile software development methodologies. Required Years Experience within financial services, banking, or regulated industries. Desired Years Experience with Python scripting and automation. Desired Years Experience with Microsoft Purview or similar data governance tools. Desired Years Experience with Master Data Management (MDM) initiatives. Desired Years Familiarity with enterprise data modernization and cloud migration programs. Desired Years Understanding of source-to-target mapping and data lineage analysis. Desired Years

• Degree and/or certifications required: NA (not specified by the client).
• 7+ years of experience in Data Engineering, Data Warehousing, or Data Management.
• Strong experience designing and developing solutions within Snowflake.
• Advanced SQL development skills.
• Experience with SSIS and enterprise ETL development.
• Experience building ELT/ETL pipelines and data integration solutions.
• Experience with Azure DevOps (ADO), CI/CD pipelines, and release management.
• Experience with data modeling, schema design, and database architecture.
• Knowledge of data governance, metadata management, and data quality frameworks.
• Experience supporting Agile software development methodologies., * Experience within financial services, banking, or regulated industries.
• Experience with Python scripting and automation.
• Experience with Microsoft Purview or similar data governance tools.
• Experience with Master Data Management (MDM) initiatives.
• Familiarity with enterprise data modernization and cloud migration programs.
• Understanding of source-to-target mapping and data lineage analysis.

Desired Experience:

• The ideal candidate will have experience providing senior-level consulting and engineering services across:

• Snowflake Database Design & Architecture
• Data Modeling & Schema Development
• Enterprise Data Migration
• Data Integration & ETL/ELT Development
• Azure DevOps Pipeline Development
• Data Governance Programs
• Data Quality Remediation
• Metadata & Lineage Management
• Agile Delivery & Release Management
• Business and Technical Requirements Analysis

Soft Skills:

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Ability to translate business requirements into technical solutions.
• Strong documentation and organizational skills.
• Ability to work independently while collaborating across multiple teams.
• Experience working with cross-functional business, analytics, QA, and engineering teams.