Data Engineer Customer 360 & Snowflake Platform

Job Description:
About the Role
Client is accelerating its data modernization journey to deliver a cloud unified, trusted, and actionable view of every customer. As a Data Engineer specializing in Customer 360, Customer Master Data, and the Snowflake Data Cloud, you will help design and build the data foundations that power personalized experiences, regulatory reporting, and enterprise analytics across lending, servicing, and marketing.
This role is ideal for an engineer who thrives at the intersection of data architecture, cloud engineering, and customer intelligence.

Key Responsibilities
Customer 360 & Master Data Engineering
Design, build, and maintain Customer 360 data models that unify identity, accounts, interactions, transactions, and servicing data across the enterprise.
Develop and enhance Customer Master Data pipelines, ensuring accuracy, survivorship logic, deduplication, and golden?record creation.
Implement identity resolution frameworks using deterministic and probabilistic matching techniques.
Partner with Marketing, Servicing, Risk, and Digital teams to translate customer insights into scalable data assets.
Snowflake Data Cloud Engineering
Build high?performance data pipelines and transformations using Snowflake, Snowpipe, Streams & Tasks, and Snowpark.
Optimize Snowflake compute usage, storage patterns, and performance tuning for large?scale customer datasets.
Implement secure data sharing, RBAC, and data governance controls aligned with Sallie Mae's compliance requirements.
Data Integration & Pipeline Development
Develop robust, scalable ETL/ELT pipelines using tools such as Snowpipe, Snowpark, python, dbt, Openflow , or equivalent.
Integrate data from internal systems (loan origination, servicing, CRM, digital engagement) and external sources (credit bureaus, marketing platforms).
Ensure data quality, lineage, and observability through automated validation and monitoring frameworks.
Collaboration & Governance
Work closely with Data Governance, Architecture, and Security teams to enforce data standards and stewardship.
Contribute to enterprise metadata, cataloging, and data quality initiatives.
Support analytics, AI/ML, and reporting teams with well?structured, trusted, and discoverable customer datasets.

Required Qualifications
Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
10+ years of experience in data engineering, cloud data platforms, or enterprise data management.
Hands?on expertise with Snowflake (Snowpipe, Streams/Tasks, Snowpark, Openflow, Cortex, performance tuning).
Strong SQL and Python skills for data transformation and automation.
Experience building Customer 360 or Customer Master Data solutions in a regulated industry.
Familiarity with MDM concepts: identity resolution, survivorship rules, hierarchy management, and data quality frameworks.
Data Modeling (Entity Relationship, Dimensional, Star/Snowflake Schema)
Experience with ETL/ELT tools and orchestration frameworks (Openflow, dbt, , etc.).
Understanding of data governance, privacy, and compliance standards (GLBA, SOC2, PCI, etc.).

Preferred Qualifications
Experience in financial services, lending, credit, or consumer banking.
Exposure to real?time or near?real?time data ingestion patterns (Kafka, Kinesis, event streaming).
Knowledge of customer analytics, segmentation, and personalization use cases.
Familiarity with cloud platforms (AWS preferred) and DevOps practices (CI/CD, Terraform, GitOps).
Experience supporting AI/ML workloads or feature engineering pipelines.

Ashok Kumar
Sr. Talent Acquisition Specialist
Email:
Web: ;br /> 4229 Lafayette Center Dr, Suite 1880, Chantilly, VA 20151