• Design and implement a scalable data warehouse or data lakehouse to support analytics, reporting, and business KPIs • Develop and maintain reliable batch and/or streaming data pipelines from internal databases and external systems • Collaborate with stakeholders to translate business requirements into efficient data models and schemas • Establish and maintain data modeling standards and best practices • Implement monitoring, data quality controls, and observability for all data workflows • Provide well-structured datasets to enable self-service analytics for BI and data teams • Document the data platform, including lineage, definitions, and contracts, to create a shared source of truth for metrics

• responsible for designing and developing data solutions that are strategic to the business and built on the latest technologies and patterns • Design and implement robust, scalable data pipelines using Databricks, Apache Spark, and Delta Lake as well as BigQuery • Design and implement efficient data pipeline frameworks, ensuring the smooth flow of data from various sources to data lakes, data warehouses, and analytical platforms • Troubleshoot and resolve issues related to data processing, data quality, and data pipeline performance • Document data infrastructure, data pipelines, and ETL processes, ensuring knowledge transfer and smooth handovers • Create automated tests and integrate them into testing frameworks • Configure and optimize Databricks workspaces, clusters, and job scheduling • Work in a Multi-cloud environment including Azure, GCP and AWS • Implement security best practices including access controls, encryption, and audit logging • Build integrations with market data vendors, trading systems, and risk management platforms • Establish monitoring and performance tuning for data pipeline health and efficiency • Collaborate with cross-functional teams to understand data requirements, identify potential data sources, and define data ingestion

**MUST RESIDE IN THE ATLANTA, GA AREA** Work at Home Opportunity Senior Data Engineer - Full-time BELAY is a growing and vibrant, Atlanta, GA-based company that offers virtual staffing solutions in the areas of Virtual Assistants, Marketing Assistants, and Financial Specialists. We are a fast-paced team of high performers that work extremely hard but also know how to have a great time. Culture is a top priority and our values are lived out daily. Who is BELAY? Click here and enjoy! Below are the position requirements. Job purpose The Senior Data Engineer will play a critical role in designing and maintaining Belay’s modern data stack. This role is responsible for building reliable, scalable data pipelines, optimizing warehouse performance, and implementing robust orchestration frameworks. The ideal candidate is highly technical, systems-minded, and experienced in Snowflake-centric environments with strong PostgreSQL and data orchestration expertise. You should be comfortable owning data infrastructure end-to-end and partnering cross-functionally with analytics, finance, and engineering teams. Duties and responsibilities As a BELAY Corporate Team member, you will professionally represent the company in all virtual and in-person interactions. You are expected to exemplify our mission, vision and core values daily, fostering a collaborative and positive team environment. Key Responsibilities Data Architecture & Engineering - Design, build, and maintain scalable ELT/ETL pipelines - Develop and optimize data models in Snowflake/PostgreSQL - Ensure data reliability, integrity, and performance across the platform - Implement best practices for data warehousing and pipeline efficiency Orchestration & Workflow Management - Build and manage workflows using Apache Airflow/Dagster - Design robust orchestration frameworks for batch and near-real-time pipelines - Monitor pipeline health and implement proactive alerting - Troubleshoot and resolve data pipeline failures quickly Database Management - Work extensively with Snowflake and PostgreSQL for source systems and operational workloads - Optimize queries and database performance - Design and maintain data ingestion patterns from Postgres to Snowflake Performance & Scalability - Tune Snowflake workloads for cost and performance efficiency - Implement partitioning, clustering, and workload management strategies - Continuously improve pipeline speed and reliability Collaboration & Strategy - Partner with analytics, finance, and product teams to support reporting needs - Translate business requirements into scalable data solutions - Mentor junior data engineers and promote best practices - Contribute to the long-term data architecture roadmap Qualifications This role requires a motivated and trustworthy self-starter with strong communication and technological skills who thrives both independently and on a team. Our ideal corporate team member is flexible, creative, well-organized and ready to roll up their sleeves to get the job done! Required Qualifications - 5+ years of experience in data engineering or related field - Strong hands-on experience with Snowflake - Strong experience with PostgreSQL - Proven expertise with Apache Airflow or Dagster and workflow orchestration - Experience building and maintaining modern ELT/ETL pipelines - Advanced SQL skills and strong data modeling experience - Experience with orchestration and pipeline monitoring best practices - Familiarity with cloud data architectures (AWS, GCP, or Azure) - Strong problem-solving and performance tuning skills - Excellent communication and documentation abilities Preferred Qualifications - Experience with dbt or similar transformation frameworks - Experience with real-time or streaming pipelines - Infrastructure-as-code experience (Terraform or similar) - Experience supporting finance or operational analytics teams - Background in high-growth or services-based companies Working conditions BELAY Corporate offers full-time remote work, requiring a dedicated, distraction-free home office for standard Monday-Friday business hours, with occasional travel for some roles. As a full-time/part-time, exempt/non-exempt W-2 employee, you'll join a vibrant, award-winning company culture where you're a valued, engaged team player in a thriving organization. Physical requirements This position does not have any physical requirements at this time. Salary Range $110,000 - $150,000 DISCLAIMER: We’ve recently seen job postings claiming to be from BELAY that aren’t affiliated with our company. Please be sure to only apply to our positions on https://belaysolutions.com/jobs/ and only reply to emails ending in @belaysolutions.com.

Employee Applicant Privacy Notice 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: We are seeking a Senior Data Engineer to join our Risk Data Team as a hands-on technical lead supporting Credit, Collections, and Fraud. This role blends deep production data engineering with formal technical and people leadership. You will own architectural decisions for the Risk data platform, define modeling standards, elevate engineering rigor, and build scalable data systems that power risk decisioning across the organization. This role exists to ensure that Risk data pipelines are reliable, well-modeled, observable, and built with long-term maintainability in mind. You will contribute directly to production data pipelines while setting standards for data modeling, dbt architecture, code quality, and observability. This is not an architect-only or strategy-only role — it requires hands-on execution and demonstrated team leadership ownership. What you’ll do: Technical Leadership - Serve as technical lead for the Risk Data Engineering team. - Own architectural decisions and data modeling strategy across the Risk domain. - Define naming conventions, modeling standards, and layered dbt architecture (staging → intermediate → marts). - Lead architecture discussions and technical planning sessions. - Conduct code reviews focused on maintainability, readability, and long-term scalability. - Translate business priorities into well-scoped, production-ready technical deliverables. Production Data Engineering - Design and build production-grade Snowflake data models. - Develop scalable dbt projects, including reusable macros and testing frameworks. - Manage Apache Airflow DAGs, including idempotency, retry logic, and failure handling. - Implement CI/CD best practices for dbt and data pipelines. - Drive automation initiatives to reduce manual operational overhead. Data Modeling - Design dimensional and relational models aligned to business definitions. - Apply modeling best practices including grain declaration, SCD strategies, and surrogate key management. - Balance normalization and performance trade-offs. - Evolve models safely as business requirements change. - Ensure all models are clearly documented with lineage and business logic. Data Quality & Observability - Own the dbt testing framework (schema tests, custom tests, generic tests). - Define and enforce freshness checks, SLA standards, and row-count validations. - Implement monitoring and observability using DataDog. - Proactively identify and reduce reliability incidents. - Establish measurable data quality SLAs in partnership with stakeholders. People Leadership - Participate in hiring, onboarding, and team building. - Run regular 1:1s and provide structured performance feedback. - Develop engineers toward ownership and technical growth. - Address underperformance early and constructively. - Foster a culture of accountability, documentation, and engineering excellence. Collaboration & Stakeholder Engagement - Partner with Risk Data Product Managers, Data Science, ML, and business stakeholders. - Communicate modeling decisions, trade-offs, and pipeline health clearly. - Influence cross-functional technical direction across Risk and platform teams. Operational Excellence - Maintain scalable, secure data systems aligned with enterprise governance standards. - Improve documentation practices including runbooks and architecture decision records. - Contribute to workforce planning and technical roadmap discussions. This role requires collaboration during core business hours. Remote candidates must be able to work cross-functionally with distributed teams. What you’ll need: - Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent work experience). - 8+ years of hands-on data engineering experience. - 2+ years of experience serving as a tech lead or leading engineers formally. - Deep expertise in dimensional and relational data modeling, including SCD strategies and grain design. - Advanced dbt experience, including layered architecture, macros, advanced testing, and semantic layer concepts. - Strong hands-on Snowflake experience, including modeling and performance optimization. - Production-level experience managing Apache Airflow DAGs. - Advanced SQL skills, including query optimization and performance tuning. - Strong Python skills for data pipeline development and automation. - Demonstrated ownership of a data quality and monitoring framework. - Experience working in regulated or high-accuracy environments. - Experience participating in hiring, onboarding, and performance management. - Strong communication skills and ability to influence cross-functional stakeholders. Nice to have: - Experience with Snowflake advanced capabilities (Snowpark, Cortex AI, ML functions). - Familiarity with LLM tooling, RAG systems, or AI-assisted data workflows. - Financial services experience (Credit, Fraud, Collections). - AWS experience (S3, Glue, Lambda) and infrastructure-as-code familiarity. - Experience implementing data governance frameworks at scale. Compensation and Benefits The base pay range for this role is listed below. 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 our 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 (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), 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. Internal Employees 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.