SoFi
Base pay range
$128,000.00/yr - $240,000.00/yr
Risk Engineering - Senior Data Engineer As a Risk Engineering - Senior Data Engineer, you will be a pivotal, hands‑on expert within our data team. Leveraging your extensive experience, you’ll design, build, and maintain highly scalable and robust data solutions that directly support our independent risk management goals. This role demands deep expertise in modern data warehousing, data modeling, and end‑to‑end pipeline development, preferably in an AI applications context. You will be an expert in our core stack: Snowflake, dbt, Apache Airflow, SQL, and Airtable.
you will be responsible for design, build and develop of our data infrastructure. You will be expected to autonomously drive and own projects from inception to completion, proactively identifying and mitigating risks. Your strategic thinking and technical leadership will not only deliver high‑impact solutions but also help shape the data strategy for the team and department. You will provide mentorship and technical guidance to other engineers, championing best practices and fostering a culture of technical excellence.
What you’ll do
Lead the architecture and implementation of complex data solutions, collaborating with risk analysts and business stakeholders to translate advanced requirements into robust data models and pipelines.
Design and build highly optimized data workflows on Snowflake, utilizing its advanced features for large‑scale financial data processing, cost optimization, and performance tuning.
Develop, manage, and optimize sophisticated ETL/ELT pipelines using dbt, Python, and Apache Airflow to ensure data integrity and address high‑exposure risks within financial datasets.
Integrate and manage data from various sources, including external data sources, into our core data platform, ensuring seamless and automated data flow for critical business applications.
Design and configure workflows based in Airtable for complex orchestrations of tasks.
Drive the strategic evolution of our modern data platform, taking full ownership of its design, maintenance, and long‑term direction.
Establish and enforce advanced data governance and quality processes, acting as a primary point of contact for escalations related to data accuracy and compliance within the financial domain.
Mentor and provide technical leadership to a team of data engineers, guiding them on best practices, complex problem solving, and career development.
Conduct expert‑level code reviews and champion data engineering best practices across the team.
Proactively troubleshoot and resolve highly complex data pipeline issues, preempting negative cross‑functional impact.
What you’ll need
4-7 years of hands‑on experience in a senior data engineering role, with a strong background in data warehousing and modern data stack architectures.
Demonstrated expertise in Snowflake, including deep knowledge of its architecture, advanced features, and performance optimization techniques for large datasets.
Expert‑level proficiency with dbt for complex data transformation, dependency management, and building production‑grade data models.
Advanced experience with Apache Airflow for orchestrating and managing mission‑critical data workflows.
Hands‑on experience with streaming data platforms – Apache Kafka (preferred).
Experience in building and maintaining CI/CD pipelines using tools such as GitHub Actions, GitLab CI/CD.
Experience with Infrastructure as Code (IaC) using Terraform (preferred), CloudFormation, or Ansible.
Familiarity with Airtable, specifically in configuring workflows, integrating it as a data source and automating data synchronization for business operations.
Mastery of SQL for complex querying, data manipulation, and performance tuning.
Experience in the banking or financial services industry is highly preferred, with a strong understanding of financial data models, compliance, and regulatory requirements.
Advanced expertise in data governance, data cataloging, metadata management, and implementing robust data quality frameworks.
Proven track record of providing technical leadership and mentoring other engineers.
Nice to have
Familiarity with data observability tools and practices.
Knowledge of other cloud‑native data platforms (e.g., AWS, GCP).
Compensation And Benefits The base pay range for this role is listed above. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit the
Benefits at SoFi
page.
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex, gender identity, gender expression, national origin, ancestry, age, physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights. SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.
#J-18808-Ljbffr
Risk Engineering - Senior Data Engineer As a Risk Engineering - Senior Data Engineer, you will be a pivotal, hands‑on expert within our data team. Leveraging your extensive experience, you’ll design, build, and maintain highly scalable and robust data solutions that directly support our independent risk management goals. This role demands deep expertise in modern data warehousing, data modeling, and end‑to‑end pipeline development, preferably in an AI applications context. You will be an expert in our core stack: Snowflake, dbt, Apache Airflow, SQL, and Airtable.
you will be responsible for design, build and develop of our data infrastructure. You will be expected to autonomously drive and own projects from inception to completion, proactively identifying and mitigating risks. Your strategic thinking and technical leadership will not only deliver high‑impact solutions but also help shape the data strategy for the team and department. You will provide mentorship and technical guidance to other engineers, championing best practices and fostering a culture of technical excellence.
What you’ll do
Lead the architecture and implementation of complex data solutions, collaborating with risk analysts and business stakeholders to translate advanced requirements into robust data models and pipelines.
Design and build highly optimized data workflows on Snowflake, utilizing its advanced features for large‑scale financial data processing, cost optimization, and performance tuning.
Develop, manage, and optimize sophisticated ETL/ELT pipelines using dbt, Python, and Apache Airflow to ensure data integrity and address high‑exposure risks within financial datasets.
Integrate and manage data from various sources, including external data sources, into our core data platform, ensuring seamless and automated data flow for critical business applications.
Design and configure workflows based in Airtable for complex orchestrations of tasks.
Drive the strategic evolution of our modern data platform, taking full ownership of its design, maintenance, and long‑term direction.
Establish and enforce advanced data governance and quality processes, acting as a primary point of contact for escalations related to data accuracy and compliance within the financial domain.
Mentor and provide technical leadership to a team of data engineers, guiding them on best practices, complex problem solving, and career development.
Conduct expert‑level code reviews and champion data engineering best practices across the team.
Proactively troubleshoot and resolve highly complex data pipeline issues, preempting negative cross‑functional impact.
What you’ll need
4-7 years of hands‑on experience in a senior data engineering role, with a strong background in data warehousing and modern data stack architectures.
Demonstrated expertise in Snowflake, including deep knowledge of its architecture, advanced features, and performance optimization techniques for large datasets.
Expert‑level proficiency with dbt for complex data transformation, dependency management, and building production‑grade data models.
Advanced experience with Apache Airflow for orchestrating and managing mission‑critical data workflows.
Hands‑on experience with streaming data platforms – Apache Kafka (preferred).
Experience in building and maintaining CI/CD pipelines using tools such as GitHub Actions, GitLab CI/CD.
Experience with Infrastructure as Code (IaC) using Terraform (preferred), CloudFormation, or Ansible.
Familiarity with Airtable, specifically in configuring workflows, integrating it as a data source and automating data synchronization for business operations.
Mastery of SQL for complex querying, data manipulation, and performance tuning.
Experience in the banking or financial services industry is highly preferred, with a strong understanding of financial data models, compliance, and regulatory requirements.
Advanced expertise in data governance, data cataloging, metadata management, and implementing robust data quality frameworks.
Proven track record of providing technical leadership and mentoring other engineers.
Nice to have
Familiarity with data observability tools and practices.
Knowledge of other cloud‑native data platforms (e.g., AWS, GCP).
Compensation And Benefits The base pay range for this role is listed above. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location. To view all of our comprehensive and competitive benefits, visit the
Benefits at SoFi
page.
SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex, gender identity, gender expression, national origin, ancestry, age, physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights. SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.
#J-18808-Ljbffr