• Build advanced data pipelines utilizing the Medallion Architecture to create high-quality data sources in Snowflake. • Leverage AI-assisted development tools to reduce manual pipeline work and explore emerging Snowflake capabilities like Cortex to support AI/ML-enabled workflows. • Build Data Applications that contribute to interactive experiences, including Streamlit-based apps, transforming Snowflake from a warehouse into a full-service data platform. • Create robust data pipelines using AWS technologies to serve specific business needs. • Design and evolve analytical data models that support BI, advanced analytics, and AI workloads. • Partner directly with Analytics and Data Science teams to translate complex business questions into well-structured, modular data assets. • Write complex Python/SQL, scripts, and stored procedures to ensure 99.95% uptime and optimize query performance for downstream consumption. • Serve as a primary advisor to the Data Management team to identify opportunities for technical improvements and automation. • Act as a leader for junior and mid-level engineers, providing direction on programming best practices, query optimization, and business tact.

• Pipeline Design and Development; Architects and builds scalable data pipelines using modern ETL (Extract, Load, Transform) tools and frameworks such as DBT (Data Build Tool), or similar. • Automates data ingestion processes from various sources including databases, APIs, and third party services. • Data Storage and Management - Designs and implements data warehousing solutions using platforms like Snowflake, Redshift, or BigQuery. • Optimizes storage solutions for performance, cost efficiency, and scalability. • Data Modeling - Develops and maintains logical and physical data models to support business analytics. • Creates and manages dimensional models, star/snowflake schemas, and other data structures. • Data Transformation - Transforms raw data into clean, organized, and analytics-ready datasets using SQL, Python, or other relevant languages. • Implements data transformation workflows to handle data cleansing, normalization, and enrichment. • Data Quality Assurance - Conducts data validation and consistency checks to ensure the accuracy and reliability of data. Implements data quality monitoring and alerting mechanisms. • Cross-Functional Collaboration - Works closely with data analysts, data scientists, and business stakeholders to gather requirements and understand their data needs. • Acts as a liaison between technical teams and business units to translate business requirements into technical specifications. • Governance Policies Implements and enforces data governance policies to ensure data privacy, security, and compliance with relevant regulations. • Defines and manages data access, controls, permissions, and audit trails. • Security Measures - Monitors and enforces data security measures to protect sensitive information from unauthorized access and breaches. • Ensures compliance with industry standards and regulations such as GDPR, CCPA, or HIPAA and others as applicable.

Role Description The Senior Data Engineer role at Spring Venture Group is an opportunity to work at the intersection of data pipelines, data modeling, analytics, AI/ML enablement, and modern cloud-native platforms, with Snowflake as your foundation. We are looking for someone who is excited to move away from building every pipeline from scratch and toward designing data products and AI-powered applications. As automation and platform capabilities advance, you will evolve from a traditional builder into a strategic architect of data-driven solutions. Essential Duties - Modern Data Platform & AI Enablement - Build advanced data pipelines utilizing the Medallion Architecture to create high-quality data sources in Snowflake. - Leverage AI-assisted development tools to reduce manual pipeline work and explore emerging Snowflake capabilities like Cortex to support AI/ML-enabled workflows. - Build Data Applications that contribute to interactive experiences, including Streamlit-based apps, transforming Snowflake from a warehouse into a full-service data platform. - Create robust data pipelines using AWS technologies to serve specific business needs. - Data Modeling & Business Impact - Design and evolve analytical data models that support BI, advanced analytics, and AI workloads. - Partner directly with Analytics and Data Science teams to translate complex business questions into well-structured, modular data assets. - Write complex Python/SQL scripts and stored procedures to ensure 99.95% uptime and optimize query performance for downstream consumption. - Leadership & Engineering Excellence - Serve as a primary advisor to the Data Management team to identify opportunities for technical improvements and automation. - Act as a leader for junior and mid-level engineers, providing direction on programming best practices, query optimization, and business tact. - Architect replacements for legacy systems with a focus on data governance and maintainable documentation, including flowcharts and clear code comments. - Support after hours and weekend releases from our internal Software Development teams. - Actively participate in code review and weekly technicals with another more senior engineer or manager. - Assist departments with time-critical SQL execution and debug database performance problems. Qualifications - Bachelor's degree in Computer Science, or a related technical field. - 4-5 years of practical production work in Data Engineering. - Expertise of the Python programming language. - Expertise of Snowflake. - Expertise of SQL, databases, & query optimization. - Must have experience in a large cloud provider such as AWS, Azure, GCP. - Advanced at reading code independently and understanding its intent. - Advanced at writing readable, modifiable code that solves business problems. - Ability to construct reliable and robust data pipelines to support both scheduled and event-based workflows. - Working directly with stakeholders to create solutions. - Mentoring junior and mid-level engineers on best practices in programming, query optimization, and business tact. Preferred Experience - Experience building or supporting Streamlit applications or similar data-driven apps. - Familiarity with Snowflake Openflow for data ingestion and orchestration. - Exposure to Snowflake Cortex or AI/ML-enabled analytics workflows. - Background in analytics engineering (dbt-style modeling, semantic layers, metrics design). Benefits - Competitive compensation. - Medical, Dental and Vision benefits after a short waiting period. - 401k matching program. - Generous paid time off program with an additional company break during the holidays. - Annual Volunteer Time Off (VTO) and a donation matching program. - Life Insurance. - Employee Assistance Program (health & well-being on and off the job). - Rewards and Recognition. - Maternity and Parental Leave. - Training program and ongoing support throughout your entire Spring Venture Group career. - Diverse, inclusive & welcoming culture. - Optional enrollment options include HSA/FSA, AD&D, Spousal/Dependent life insurance, Short Term/Long Term Disability, Travel Assist, and Legal plans.

• Define and evolve the Accelerant Data Platform by gathering stakeholder requirements. • Identify opportunities to deliver value through data-driven solutions enabling Risk Exchange efficiency. • Collaborate with Product Managers, Engineers, and Designers to deliver high-quality solutions. • Develop and own roadmap for data ingestion and consumption with Outcome and Key Results (OKRs). • Communicate strategy and platform outcomes to various levels within the company.