Senior Compliance Data Analyst

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Who we are:

Shape a brighter financial future with us.

Together with our members, we’re changing the way people think about and interact with personal finance.

We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.

The role:

SoFi runs on data! We are seeking a highly motivated Sr. Data Analyst to join our Compliance data analytics team. As a Sr. Data Analyst at SoFi, you will play a pivotal role in ensuring our organization's commitment to regulatory compliance, integrity, and innovation. 

As a Sr. Data Analyst you will lead the vision and strategy to utilize the data-mart to provide oversight and guidance regarding business products, services, and processes, ensuring operational and regulatory compliance. You will work alongside our experienced team of data analyst(s), data engineer(s) and utilize cutting edge-technology to monitor and assess compliance risks.

This role requires you to live at the cross section of data engineering and analytics. Collaborating with data engineering teams, and data analysts and managing the data mart will be integral to the success of this role.

A talented, enthusiastic, detail-oriented, and experienced Sr. Data Analyst who knows how to take on big data challenges in an agile way. This includes big data design and analysis, data modeling, and development, deployment, and operations of big data pipelines. Participates in the development of some of the most critical data pipelines and data sets, and expands  self-service data knowledge and capabilities. 

What you’ll do: 

• Collaborate with cross-functional teams, such as data analytics, data scientists, software engineers, and business stakeholders, to understand data requirements and deliver solutions that meet Compliance needs. Effectively communicate complex technical concepts to non-technical stakeholders.

• Design and develop robust data architectures and data pipelines to support data ingestion, processing, storage, and retrieval. Evaluate and select appropriate technologies, frameworks, and tools to build scalable and reliable data infrastructure.

• Optimize data engineering systems and processes to handle large-scale data sets efficiently. Design solutions that can scale horizontally and vertically.

• Enforce data governance policies and practices to maintain data integrity, security, and compliance with relevant regulations. Collaborate with data governance and security teams to implement robust data protection mechanisms and access controls.

• Design, develop, and manage periodic departmental reports and dashboards.

• Develop and maintain Metrics, Key Risk Indicators (KRIs), trending, and dashboards.

• Assist Regulatory Compliance, AML, and QA teams with data analysis, reporting, and modeling-related activities as needed.

• Coordinate with various business teams for regulatory exams and internal audits, providing requested data as needed.

• Collaborate with Data Owners, Data Stewards, and Data Engineering teams to identify data elements, populate metadata, curate catalog, manage glossaries, and evaluate data quality.

• Actively participate in the team meetings and contribute to discussions on technology, design, and implementation.

What you’ll need:

• A bachelor's degree in Computer Science, Data Science, Engineering, or a related field.

• 4+ years of experience in data engineering and analytics technical strategy. 

• High proficiency in data engineering technologies including Snowflake, PostgreSQL, Python, SQL, GitLab, AWS, Airflow, and DBT.

• Proficiency in relational database platforms and cloud database platforms such as Snowflake, Redshift, or GCP.

• Thorough knowledge of data modeling, database design, data architecture principles, and data operations.

• Strong in Python and/or another data centric lang