Senior Data Engineer (Hybrid)
About The Position
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.
Requirements
- 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.
Nice To Haves
- 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.
Responsibilities
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
