SLM
Join Sallie Mae
When you join Sallie, you become a champion for all students. Sallie's Education Services team is a diverse group of growth-obsessed entrepreneurs, data analysts, engineers, and developers with a passion for imagining and building scalable businesses for students and families on their unique journey to-through and immediately after higher education. We're on a mission to revolutionize how students and their families plan, pay, and complete this journey with confidence. Join a team of seekers, challengers, and creative thinkers to change the way students plan for their future for the better. A little bit about us: Would you like to work in an exciting fast-paced start-up place with the backing of a household name company like Sallie Mae to help millions of people meet their educational needs every day? Together, we're connected by the same driveto be a champion for all students and help them make smart decisions with confidence. Do more than join somethingchange somethingfor students, for future generations, and for the future of education. Our new venture, Sallie
SM , is looking for people like you to be the founding members who will define the future of education services for students and their families in the US. As the first education solutions company, we're creating products and experiences that help students when they need it most. We're connecting students to free money for school, providing tools and resources to plan for college, sharing inside advice on campus life, and so much more. What You'll Contribute We are seeking a Director, Data Engineering with a proven track record of designing and building complex, scalable data products that drive business outcomes and support organizational growth. This is a high-impact, hands-on role responsible for developing robust data infrastructure, analytics solutions, and customer-facing prototypes that power operational insights and strategic decision-making. As a Sr. DE, you will collaborate closely with product managers, solution architects, software engineers, data scientists, and external partners to deliver data-driven technology solutions. You will lead the design and implementation of modern data architectures, simplify legacy systems, and develop scalable pipelines and models to support the evolving needs of our fintech platform. You will be instrumental in shaping our data ecosystem, applying cutting-edge tools in machine learning and AI to accelerate development and innovation. With ownership over the full development lifecyclefrom architecture to deploymentyou will play a critical role in solving high-scale engineering challenges and ensuring the long-term success of our data products and services. What You'll Do Data Warehousing and Architecture (Snowflake):
Lead the end-to-end architecture, implementation, and ongoing management of the enterprise data warehouse using Snowflake. Design scalable and secure data models that integrate disparate data sources while optimizing for performance, cost-efficiency, and data quality. Ensure high levels of data integrity, consistency, and availability to support accurate reporting and advanced analytics. ETL/ELT Pipeline Development and Automation:
Design, build, and maintain robust ETL/ELT pipelines using Snowflake, dbt, and other modern data integration tools. Automate and optimize data ingestion and transformation processes to support real-time and batch data needs. Drive continuous improvement of data workflows, ensuring reliability, scalability, and low-latency access to high-quality data. Cross-Functional Data Enablement:
Collaborate with cross-functional stakeholdersincluding marketing, product, finance, compliance, operations, and engineeringto gather data requirements and translate them into scalable technical solutions. Serve as a strategic partner and trusted advisor on data architecture, tooling, and infrastructure capabilities. Data Governance, Quality, and Security:
Champion data governance initiatives by implementing and enforcing standards around data quality, cataloging, lineage, and stewardship. Ensure all data practices align with industry regulations and internal policies, particularly around data privacy (e.g., GDPR, CCPA) and security. Establish monitoring and alerting systems to proactively identify and resolve data issues. Support for Advanced Analytics and Machine Learning:
Partner with data science and analytics teams to prepare, clean, and structure datasets for advanced modeling, experimentation, and AI/ML initiatives. Build pipelines and feature stores that enable reproducibility, version control, and scalable deployment of machine learning models into production environments. Innovation and Best Practices:
Stay ahead of emerging technologies and industry trends in data engineering, cloud computing, and analytics. Evaluate and recommend new tools, frameworks, and methodologies to improve the efficiency, scalability, and robustness of the data platform. Mentor junior engineers and help establish a culture of engineering excellence and data-driven decision-making. What You Have Minimum education, skills, and experience required. BS in Data Science, Computer Science, Software Engineering, Information Technology, Business Analytics, or a related technical field; or equivalent practical experience in data engineering roles. 7+ years of professional experience in data engineering, including hands-on design, development, and maintenance of scalable data pipelines, data warehousing solutions, and ETL/ELT processes. Expert-level experience with Snowflake, including performance tuning, architecture best practices, data ingestion techniques, security configuration, and optimization of compute and storage resources. Solid understanding of data modeling techniques (e.g., star/snowflake schemas, normalization/denormalization), and experience implementing models for both transactional and analytical workloads. Demonstrated experience with distributed, multi-tiered systems and modern data architecture practices, including batch and real-time data processing frameworks. Experience with modern data visualization tools and platforms (e.g., Tableau, Power BI, Looker) to support data democratization and decision-making across the organization. Working knowledge of data governance principles, including data quality, cataloging, lineage, and compliance with data security and privacy standards (e.g., SOC 2, GDPR, CCPA). Proven ability to collaborate cross-functionally with engineering, product, analytics, and business stakeholders to translate data needs into scalable solutions. Exceptional problem-solving and analytical skills, with a deep understanding of data structures, algorithms, and a data-driven approach to identifying opportunities and solving complex business challenges. Proven track record of delivering high-quality solutions in a fast-paced, evolving environment with competing priorities and tight deadlines. Excellent communication skills, both written and verbal, with the ability to present technical concepts clearly to technical and non-technical stakeholders. Preferred education, skills, and experience. Hands-on experience with cloud data ecosystems such as AWS (e.g., Redshift, Glue, S3, Lambda), GCP (e.g., BigQuery, Dataflow), or Azure (e.g., Synapse, Data Factory). Familiarity with machine learning and artificial intelligence pipelines, and the integration of model outputs into data workflows and applications. Experience with modern data orchestration tools (e.g., Airflow, dbt, Prefect) and CI/CD pipelines for data infrastructure. Experience with non-relational databases and data stores, such as MongoDB, Redis, Cassandra, graph databases (e.g., Neo4j), or object storage systems. Proficiency with statistical analysis tools and programming languages, including Python, R, MATLAB, SAS, or Stata. Experience working in a fintech or regulated industry environment, with knowledge of industry-specific compliance and risk considerations. Exposure to customer engagement platforms or marketing technologies, such as HubSpot, Segment, or Salesforce Marketing Cloud, especially for data integration or reporting use cases. The Americans with Disabilities Act The Americans with Disabilities Act of 1990 (ADA) prohibits discrimination by employers, in compensation and employment opportunities, against qualified individuals with disabilities who, with or without reasonable accommodation, can perform the "essential functions" of a job. A function may be essential for any of several reasons, including: the job exists to perform that function, the employee holding the job was hired for his/her expertise in performing the function, or only a limited number of employees are available to perform that function. Our Benefits Take Care of the Whole YouSo You Can Build Your Work Around Your Life (Not the Other Way Around!)
Competitive base salaries
Bonus incentives
Generous PTO, Floating Holidays and 1
When you join Sallie, you become a champion for all students. Sallie's Education Services team is a diverse group of growth-obsessed entrepreneurs, data analysts, engineers, and developers with a passion for imagining and building scalable businesses for students and families on their unique journey to-through and immediately after higher education. We're on a mission to revolutionize how students and their families plan, pay, and complete this journey with confidence. Join a team of seekers, challengers, and creative thinkers to change the way students plan for their future for the better. A little bit about us: Would you like to work in an exciting fast-paced start-up place with the backing of a household name company like Sallie Mae to help millions of people meet their educational needs every day? Together, we're connected by the same driveto be a champion for all students and help them make smart decisions with confidence. Do more than join somethingchange somethingfor students, for future generations, and for the future of education. Our new venture, Sallie
SM , is looking for people like you to be the founding members who will define the future of education services for students and their families in the US. As the first education solutions company, we're creating products and experiences that help students when they need it most. We're connecting students to free money for school, providing tools and resources to plan for college, sharing inside advice on campus life, and so much more. What You'll Contribute We are seeking a Director, Data Engineering with a proven track record of designing and building complex, scalable data products that drive business outcomes and support organizational growth. This is a high-impact, hands-on role responsible for developing robust data infrastructure, analytics solutions, and customer-facing prototypes that power operational insights and strategic decision-making. As a Sr. DE, you will collaborate closely with product managers, solution architects, software engineers, data scientists, and external partners to deliver data-driven technology solutions. You will lead the design and implementation of modern data architectures, simplify legacy systems, and develop scalable pipelines and models to support the evolving needs of our fintech platform. You will be instrumental in shaping our data ecosystem, applying cutting-edge tools in machine learning and AI to accelerate development and innovation. With ownership over the full development lifecyclefrom architecture to deploymentyou will play a critical role in solving high-scale engineering challenges and ensuring the long-term success of our data products and services. What You'll Do Data Warehousing and Architecture (Snowflake):
Lead the end-to-end architecture, implementation, and ongoing management of the enterprise data warehouse using Snowflake. Design scalable and secure data models that integrate disparate data sources while optimizing for performance, cost-efficiency, and data quality. Ensure high levels of data integrity, consistency, and availability to support accurate reporting and advanced analytics. ETL/ELT Pipeline Development and Automation:
Design, build, and maintain robust ETL/ELT pipelines using Snowflake, dbt, and other modern data integration tools. Automate and optimize data ingestion and transformation processes to support real-time and batch data needs. Drive continuous improvement of data workflows, ensuring reliability, scalability, and low-latency access to high-quality data. Cross-Functional Data Enablement:
Collaborate with cross-functional stakeholdersincluding marketing, product, finance, compliance, operations, and engineeringto gather data requirements and translate them into scalable technical solutions. Serve as a strategic partner and trusted advisor on data architecture, tooling, and infrastructure capabilities. Data Governance, Quality, and Security:
Champion data governance initiatives by implementing and enforcing standards around data quality, cataloging, lineage, and stewardship. Ensure all data practices align with industry regulations and internal policies, particularly around data privacy (e.g., GDPR, CCPA) and security. Establish monitoring and alerting systems to proactively identify and resolve data issues. Support for Advanced Analytics and Machine Learning:
Partner with data science and analytics teams to prepare, clean, and structure datasets for advanced modeling, experimentation, and AI/ML initiatives. Build pipelines and feature stores that enable reproducibility, version control, and scalable deployment of machine learning models into production environments. Innovation and Best Practices:
Stay ahead of emerging technologies and industry trends in data engineering, cloud computing, and analytics. Evaluate and recommend new tools, frameworks, and methodologies to improve the efficiency, scalability, and robustness of the data platform. Mentor junior engineers and help establish a culture of engineering excellence and data-driven decision-making. What You Have Minimum education, skills, and experience required. BS in Data Science, Computer Science, Software Engineering, Information Technology, Business Analytics, or a related technical field; or equivalent practical experience in data engineering roles. 7+ years of professional experience in data engineering, including hands-on design, development, and maintenance of scalable data pipelines, data warehousing solutions, and ETL/ELT processes. Expert-level experience with Snowflake, including performance tuning, architecture best practices, data ingestion techniques, security configuration, and optimization of compute and storage resources. Solid understanding of data modeling techniques (e.g., star/snowflake schemas, normalization/denormalization), and experience implementing models for both transactional and analytical workloads. Demonstrated experience with distributed, multi-tiered systems and modern data architecture practices, including batch and real-time data processing frameworks. Experience with modern data visualization tools and platforms (e.g., Tableau, Power BI, Looker) to support data democratization and decision-making across the organization. Working knowledge of data governance principles, including data quality, cataloging, lineage, and compliance with data security and privacy standards (e.g., SOC 2, GDPR, CCPA). Proven ability to collaborate cross-functionally with engineering, product, analytics, and business stakeholders to translate data needs into scalable solutions. Exceptional problem-solving and analytical skills, with a deep understanding of data structures, algorithms, and a data-driven approach to identifying opportunities and solving complex business challenges. Proven track record of delivering high-quality solutions in a fast-paced, evolving environment with competing priorities and tight deadlines. Excellent communication skills, both written and verbal, with the ability to present technical concepts clearly to technical and non-technical stakeholders. Preferred education, skills, and experience. Hands-on experience with cloud data ecosystems such as AWS (e.g., Redshift, Glue, S3, Lambda), GCP (e.g., BigQuery, Dataflow), or Azure (e.g., Synapse, Data Factory). Familiarity with machine learning and artificial intelligence pipelines, and the integration of model outputs into data workflows and applications. Experience with modern data orchestration tools (e.g., Airflow, dbt, Prefect) and CI/CD pipelines for data infrastructure. Experience with non-relational databases and data stores, such as MongoDB, Redis, Cassandra, graph databases (e.g., Neo4j), or object storage systems. Proficiency with statistical analysis tools and programming languages, including Python, R, MATLAB, SAS, or Stata. Experience working in a fintech or regulated industry environment, with knowledge of industry-specific compliance and risk considerations. Exposure to customer engagement platforms or marketing technologies, such as HubSpot, Segment, or Salesforce Marketing Cloud, especially for data integration or reporting use cases. The Americans with Disabilities Act The Americans with Disabilities Act of 1990 (ADA) prohibits discrimination by employers, in compensation and employment opportunities, against qualified individuals with disabilities who, with or without reasonable accommodation, can perform the "essential functions" of a job. A function may be essential for any of several reasons, including: the job exists to perform that function, the employee holding the job was hired for his/her expertise in performing the function, or only a limited number of employees are available to perform that function. Our Benefits Take Care of the Whole YouSo You Can Build Your Work Around Your Life (Not the Other Way Around!)
Competitive base salaries
Bonus incentives
Generous PTO, Floating Holidays and 1