Role Overview
We are seeking a hands-on Senior Data Engineer for a contract opportunity supporting key enterprise data initiatives within a financial services environment.
The successful candidate will design, build and maintain data migration, integration and pipeline solutions, with a focus on Snowflake, AWS and modern data engineering practices.
Initial priorities include the Collections and LoanPro programs, with responsibility for preparing and migrating data into target platforms and establishing ongoing batch and change data capture (CDC) integrations into Snowflake.
Working closely with business stakeholders, application teams, vendors, Data Architecture and Analytics, the successful candidate will translate business and technical requirements into reliable, scalable data solutions that meet program timelines and quality standards.
The role will also contribute to broader enterprise data initiatives, including single-view-of-customer capabilities, canonical data models, reusable data assets and semantic layers that support advanced analytics and AI-enabled use cases.
We are looking for a technically strong professional who can take ownership of deliverables, solve complex data engineering challenges and work effectively across business and technology teams.
Key Responsibilities
Data Migration & Program Delivery
- Investigate and profile data across existing platforms and third-party sources to understand data structures, business rules, dependencies and quality issues.
- Collaborate with business stakeholders, application teams and vendors to define data requirements, source-to-target mappings, transformation rules and validation criteria.
- Develop migration datasets and processes to consolidate, cleanse and transform source data to meet target platform requirements.
- Execute and support migration activities, including trial loads, data validation, reconciliation, defect resolution and production cutover.
- Identify and resolve data discrepancies, working with relevant teams to investigate root causes and implement remediation.
- Manage assigned deliverables and dependencies against project milestones, proactively communicating progress, risks and issues requiring escalation.
Data Integration & Engineering
- Design, build and maintain reliable data pipelines and integrations into Snowflake using appropriate integration tools and AWS services.
- Implement batch, incremental and change data capture (CDC) pipelines based on source-system capabilities and business requirements.
- Develop transformations and datasets across ingestion, curated, Gold and reporting layers.
- Collaborate with Data Architecture and Analytics to align data structures, relationships, business definitions and downstream consumption requirements.
- Implement data quality checks, reconciliation, monitoring, error handling and recovery processes.
- Troubleshoot pipeline failures, data discrepancies and performance issues.
- Support production deployments, operational readiness and ongoing maintenance.
Enterprise Data Enablement
- Build reusable pipelines, transformations and datasets that support multiple programs and business requirements.
- Contribute to single-view-of-customer capabilities and the implementation of canonical data models in alignment with established architecture standards.
- Support the development of trusted datasets and semantic layers for self-service analytics and AI-enabled data access.
- Identify opportunities to improve data quality, reuse existing data assets and establish consistent engineering patterns.
Engineering Practices & Collaboration
- Take ownership of assigned deliverables from requirements clarification and technical design through development, testing, deployment and operational handover.
- Adhere to established architecture, security, data governance and software development standards.
- Maintain accurate source-to-target mappings, technical documentation, data definitions and operational guidance.
- Apply version control, automated testing, CI/CD and deployment best practices.
- Participate in technical design discussions and code reviews.
- Collaborate with internal teams and external delivery partners to resolve issues, manage dependencies and meet delivery commitments.
Required Skills & Experience
- Strong hands-on experience designing and delivering production data pipelines and integrations using Snowflake.
- Advanced SQL skills, including complex transformations, data analysis, troubleshooting and query performance optimization.
- Proven experience delivering data migrations, including source analysis, mapping, transformation, validation and reconciliation.
- Experience implementing batch, incremental and/or change data capture (CDC) pipelines.
- Practical experience with AWS services supporting data storage, integration, processing or orchestration.
- Experience with dbt, Snowflake Openflow, Apache NiFi or comparable data integration and transformation tools.
- Ability to translate business and technical requirements into effective data engineering solutions.
- Solid understanding of data warehousing concepts, curated datasets and reporting layers.
- Experience with version control, CI/CD, testing, monitoring and production support.
- Strong analytical, problem-solving and communication skills, with the ability to manage dependencies and deliver against project timelines.
Preferred Skills & Experience
- Python experience for data processing, integration or automation.
- Experience working with lending, collections, customer or other financial services data.
- Exposure to customer data integration, single-view-of-customer capabilities or canonical data models.
- Experience developing semantic layers or working with Snowflake capabilities supporting AI-enabled analytics.
What We're Looking For
The ideal candidate combines strong technical execution with a practical, delivery-focused mindset. They can work independently, take accountability for their deliverables, navigate complex data challenges and collaborate effectively with business and technology stakeholders.
- Experience delivering data migrations and production-grade Snowflake pipelines in a complex enterprise environment will be particularly valuable.
