Senior Data Engineer

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Key Responsibilities

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• Assess existing SQL Server (Atlas) and Snowflake environments to identify pipeline gaps, data quality issues, and structural inefficiencies

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• Build and maintain data pipelines supporting the Operational Data Store (ODS), including ingestion, transformation, and loading of key business entities

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• Implement, version-control, and enforce data dictionary standards, logical/physical entity models, and naming conventions established by the Data Architect

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• 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

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• Manage database schema migrations as code using tools such as dbt, Schemachange, Flyway, or Terraform

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• Execute the batch-to-API migration roadmap — re-engineering Informatica/EDW batch flows to consume FDR APIs

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• Implement automated data quality frameworks, testing validations (e.g., dbt tests, Great Expectations), and data parity reconciliation routines between legacy and new ODS environments

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• Collaborate with domain teams to engineer pipelines for customer, loan, payment, and interaction data entities

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• Apply Snowflake best practices in structuring schemas, managing compute, and separating analytical from operational workloads

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• Partner with the internal data architect and downstream consumers to ensure data accuracy, lineage, and observability across the platform

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• Leverage generative AI tools (e.g., coding assistants, LLMs) to accelerate pipeline development, optimize query performance, write documentation, and generate automated tests

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Must-Have Skills

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• 7+ years in data engineering roles with a strong focus on pipeline development, CI/CD setup, and database modeling

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• Strong programming skills in SQL (Sql Server and Postgres) and Python for data engineering, automation, and pipeline development

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• Proficiency in Snowflake — including schema design, performance tuning, and data loading patterns

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• Hands-on experience building DevOps/DataOps pipelines (Git, CI/CD tools, automated deployment strategies)

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• Hands-on experience with database migration tools / schema management systems (e.g., dbt, Schemachange, Flyway)

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• Hands-on experience with ETL/ELT tools and batch processing (Informatica experience strongly preferred)

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• Solid understanding of ODS concepts, dimensional modeling, and managing data dictionaries

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• Experience integrating with REST/API-based data sources as part of modernization or migration efforts

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• Demonstrated experience using Generative AI coding assistants (e.g., Copilot, ChatGPT, Gemini) to enhance coding productivity, write tests, and troubleshoot complex SQL/Python scripts

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• Background in financial services or lending domain

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Nice to Have

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• Experience with modern orchestrators (e.g., Apache Airflow, Prefect, Dagster) or Snowflake-native orchestration (Tasks, Dynamic Tables)

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• Familiarity with deploying semantic layers or metadata-driven catalog systems (Collibra, Alation) to support downstream AI/ML and Natural Language query agents

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• Experience working with FDR or similar loan servicing platforms

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• Familiarity with data mesh principles and domain-oriented data ownership

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• Exposure to AI/ML data pipeline requirements and feature engineering

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• Experience with data governance and cataloguing tools (Collibra, Alation, etc.)

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• Background in student lending or consumer finance