Assess existing SQL Server (Atlas) and Snowflake environments to identify pipeline gaps, data quality issues, and structural inefficiencies
Build and maintain data pipelines supporting the Operational Data Store (ODS), including ingestion, transformation, and loading of key business entities
Implement, version-control, and enforce data dictionary standards, logical/physical entity models, and naming conventions established by the Data Architect
Design, implement, and maintain CI/CD pipelines (e.g., GitHub Actions, GitLab CI) to automate the deployment of Snowflake schemas, database structures, and pipeline code
Manage database schema migrations as code using tools such as dbt, Schemachange, Flyway, or Terraform
Execute the batch-to-API migration roadmap - re-engineering Informatica/EDW batch flows to consume FDR APIs
Implement automated data quality frameworks, testing validations (e.g., dbt tests, Great Expectations), and data parity reconciliation routines between legacy and new ODS environments
Collaborate with domain teams to engineer pipelines for customer, loan, payment, and interaction data entities
Apply Snowflake best practices in structuring schemas, managing compute, and separating analytical from operational workloads
Partner with the internal data architect and downstream consumers to ensure data accuracy, lineage, and observability across the platform
Leverage generative AI tools (e.g., coding assistants, LLMs) to accelerate pipeline development, optimize query performance, write documentation, and generate automated tests
Must-Have Skills
7+ years in data engineering roles with a strong focus on pipeline development, CI/CD setup, and database modeling
Strong programming skills in SQL (Sql Server and Postgres) and Python for data engineering, automation, and pipeline development
Proficiency in Snowflake - including schema design, performance tuning, and data loading patterns
Hands-on experience with database migration tools / schema management systems (e.g., dbt, Schemachange, Flyway)
Hands-on experience with ETL/ELT tools and batch processing (Informatica experience strongly preferred)
Solid understanding of ODS concepts, dimensional modeling, and managing data dictionaries
Experience integrating with REST/API-based data sources as part of modernization or migration efforts
Demonstrated experience using Generative AI coding assistants (e.g., Copilot, ChatGPT, Gemini) to enhance coding productivity, write tests, and troubleshoot complex SQL/Python scripts
Background in financial services or lending domain
Nice to Have
Experience with modern orchestrators (e.g., Apache Airflow, Prefect, Dagster) or Snowflake-native orchestration (Tasks, Dynamic Tables)
Familiarity with deploying semantic layers or metadata-driven catalog systems (Collibra, Alation) to support downstream AI/ML and Natural Language query agents
Experience working with FDR or similar loan servicing platforms
Familiarity with data mesh principles and domain-oriented data ownership
Exposure to AI/ML data pipeline requirements and feature engineering
Experience with data governance and cataloguing tools (Collibra, Alation, etc.)
