• Build and maintain high-throughput ETL/ELT pipelines • Drive the adoption of dbt for transformation and PySpark • Implement "Data SLAs" and build monitoring systems • Work closely with the BI team and Data Scientists • Deep-dive into SQL and Spark query plans for optimization • Implement a local development workflow with DuckDB • Build specialized pipelines for client reporting • Explore use of DuckDB for internal tools or edge processing

Have an opportunity to help shape how a major Finance organization makes decisions — and grow your career while you do it. You will combine best-in-class business intelligence with applied artificial intelligence to deliver insights that reach senior leaders. You will help move the team beyond static dashboards toward natural-language, decision-ready experiences. This is a high-visibility, hands-on role for a technically strong contributor who wants to build durable solutions and develop their craft. It begins as an individual contributor position with room to take on increasing scope and technical ownership as the portfolio grows. As a Data Visualization Sr Associate on the Finance Data & Insights team, you will help deliver executive-grade insights and artificial-intelligence-enabled experiences that help senior Finance leaders make faster, higher-confidence decisions. You will contribute across the full lifecycle of our visualization and conversational analytics products — from framing the problem and modeling the data to designing the experience, deploying it, and driving adoption. You will help build guided self-service and natural-language tools that let leaders explore performance drivers, scenarios, and risk-and-return trade-offs in plain language. You will partner closely with Finance, Product, Data Engineering, and platform teams to keep everything secure, compliant, and production-grade. Most importantly, you will help translate leadership questions into trusted data products and high-performing experiences. You will support the modernization of the team's analytics delivery, partnering across Finance, Product, Data Engineering, and platform teams to ensure solutions are secure, compliant, and production-grade. You will contribute hands-on to the technical translation from leadership questions into governed data products and performant experiences. Job Responsibilities - Support the analytics product portfolio for Finance, including backlog, prioritization, and value delivery. - Design and deliver executive-grade dashboards and narratives in ThoughtSpot, Databricks, and Tableau, aligned to governed metrics and finance definitions. - Build artificial-intelligence-enabled conversational analytics using Databricks Genie and ThoughtSpot Spotter, including interaction design, evaluation, and monitoring. - Partner with Data Engineering to help ensure data quality, timeliness, lineage, and scalable architecture, validating semantic models and metric logic hands-on. - Implement controls suited to a regulated environment, including access controls, privacy-by-design, and alignment to model, data, and operational risk expectations. - Support adoption through enablement, training, documentation, and measurable usage tracking with clear leadership feedback loops. - Contribute to senior Finance forums, helping frame insights, drivers, and recommended actions concisely. - Follow technical and delivery standards and support analysts and visualization specialists through collaboration and review. Required qualifications, capabilities, and skills: - Experience delivering data solutions and analytics for Finance stakeholders. - Demonstrated production delivery in Tableau and/or ThoughtSpot, including dashboard design and metric architecture. - Hands-on experience with the Databricks platform, including contributing to technical design discussions on semantic modeling and performance. - Advanced SQL skills and the ability to validate datasets and logic end-to-end. - Demonstrated ability to translate business questions into analytical products, including requirements definition and acceptance criteria. - Experience contributing to and maintaining a backlog based on stakeholder needs. - Experience applying quality standards and collaborating with analysts. - Demonstrated risk and control practices in a regulated environment, including data access governance and change management for reporting. Preferred qualifications, capabilities, and skills: - Experience building conversational analytics or natural-language query experiences, including quality evaluation and guardrails. - Experience with Databricks Genie and/or ThoughtSpot Spotter to enable governed self-service. - Proficiency with Alteryx for workflow automation and repeatable data preparation. - Finance domain knowledge (profitability drivers, advisor metrics, client flows, assets under management, pricing/fees, and forecasting). - Experience supporting analytics governance, such as metric-definition standards, release management, and adoption measurement. - Familiarity with model risk management and artificial-intelligence governance in regulated environments. - Exposure to team collaboration or peer mentoring. About UsChase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. Equal Opportunity Employer/Disability/Veterans About the Team Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

• Define and evolve the enterprise data architecture across ingestion, storage, transformation, semantic modeling, and consumption layers, with Snowflake as the core platform. • Design and own the medallion architecture across Bronze, Silver, Gold, and Semantic layers, establishing clear standards for schema design, object naming, access patterns, and layer boundaries. • Lead semantic model strategy by defining how key business entities, metrics, and KPIs are represented in Snowflake and surfaced through BI tools. • Drive architectural decisions across the modern data stack, including ingestion through Fivetran, transformation through Coalesce and related conventions, and BI delivery through Tableau. • Identify and resolve performance, scalability, and cost-efficiency challenges in Snowflake, including query optimization, clustering strategy, virtual warehouse sizing, and storage management. • Design the platform to serve as a reliable enterprise context layer for AI by establishing patterns for metadata enrichment, semantic data modeling, contextual retrieval, and curated data products.

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.