• Partner with the AI Technical Product Manager to support data-driven decision-making across AI initiatives • Analyze datasets to assess the potential functional and business impact of proposed features • Define success metrics and measure post-implementation performance to evaluate actual impact • Provide actionable insights that inform product roadmap, prioritization, and ROI • Collaborate with ML Engineers to identify machine learning opportunities using proprietary datasets • Design and execute experiments (A/B testing, hypothesis testing) to validate product and AI feature effectiveness • Build dashboards, reports, and visualizations to communicate insights to technical and non-technical stakeholders • Ensure data quality, integrity, and proper usage across projects.

Position: Sr. Data Engineer Job Description: Arrow Electronics is a global provider of products, services, and solutions to industrial and commercial users of electronic components and enterprise computing solutions. Arrow Electronics guides innovation forward for over 220,000 leading technology manufacturers and service providers. With 2024 sales of $27.9 billion, Arrow develops technology solutions that improve business and daily life. The company maintains 228 locations worldwide with over 85 countries served. A Fortune 154 company with 21,500 employees worldwide, Arrow brings technology solutions to a breadth of markets, including telecommunications, information systems, transportation, medical, industrial, and consumer electronics. Arrow provides specialized services and expertise across the entire product lifecycle. Arrow does this by connecting customers to the right technology at the right place, time, and price. Arrow provides extraordinary value to customers and suppliers - the best technology companies in the world - and connects them through the company's industry-leading services. Join the data engineering team to participate and collaborate in the global modernization of the tools and solutions. Be part of a global team. How to Apply: Internal Employees: Please submit your updated resume in English and ensure you use only your Arrow email address. External Candidates: Please submit your updated resume in English. What You'll Be Doing: - Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and data integration solutions with moderate independence. - Translate business requirements into technical designs and contribute to solution architecture discussions. - Build and enhance business-to-business (B2B) integrations and internal data processing workflows. - Diagnose and resolve data quality issues, pipeline failures, and performance bottlenecks; propose optimizations. - Develop clear documentation for data models, workflows, and engineering solutions. - Collaborate with cross-functional teams including data architects, analysts, application developers, and business stakeholders to ensure effective data delivery. - Contribute to project workstreams, ensuring tasks are delivered with quality and within timelines. - Adhere to and promote engineering best practices, coding standards, and data governance guidelines. What We Are Looking For: - +5 years of experience in similar roles. - Strong programming experience in Python AND/OR Java. - Advanced SQL Experience. - +4 years of experience with Databricks. - Experience in Agile work environment. The Skills That Will Help You Succeed Even More: (Optional) - Experience with Kafka, Eventhub, kinesis. - Experience implementing data quality frameworks. - Exposure to API-based data integrations. What’s In It For You : At Arrow, we recognize that financial rewards and great benefits are important aspects of an ideal job. That’s why we offer competitive financial compensation, including various compensation plans, and a solid benefits package. - 30 days of Christmas bonus - 40% vacation premium - 12 vacation days plus 2 floating days, your birthday and sick days. - Vision and Dental Assistance - Life Insurance - Healthcare Insurance - 10% Food/Pantry Vouchers - Restaurant Vouchers - 13% Savings Fund - Growth Opportunities, and more! Apply now! #LI-FS1 #LI-Remote Annual Hiring Range/Hourly Rate: $69,350.00 - $80,000.00 MXN Monthly Actual compensation offer to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level. The pay ratio between base pay and target incentive (if applicable) will be finalized at offer. Location: MX-Mexico (Remote Employees) CST/CDT Time Type: Full time Job Category: Information Technology EEO Statement: Please be sure to include all work history on your resume including: temporary employment, work as a contractor, other subsidiaries, changes in entities legal name, etc. Arrow is an equal opportunity employer. All applicants will be considered for employment without attention to religion, gender, age, sexual orientation, gender identity or national origin. (EEO policy Mexico)

Are you a talented Data Engineer looking to join a scaling startup? Do you enjoy being part of a team that makes a real difference to the success of small business owners? If you are ready to help evolve and scale the data infrastructure that empowers entrepreneurs, read on. Overview: FundThrough is looking for a Data Engineer to not only build data pipelines but also extend the next generation of our data tools. As a Data Engineer, you will develop a clear sense of connection and purpose with our organization and leadership; Data Engineering is the eyes through which we see our  product’s success and opportunities. As a member of the Data Science & Engineering team you will contribute to a variety of projects and technologies that include microservices, event-driven design, analytics, ML modeling, tooling, services, and more. The ideal candidate is self-motivated, highly collaborative, someone who thrives in a fast paced environment, and gets excited to work with the latest stack of technologies on rapidly growing products. About the company: FundThrough is a leading fintech company accelerating cash flow and enabling growth for small and medium-sized businesses. Based in Toronto and operating across North America, FundThrough’s AI-powered invoice funding platform gives B2B businesses fast, customized funding offers to get their invoices paid in a few days, rather than a few months. What you will do: - Collaborative Architecture: Partner with the team to provide architectural suggestions and formal proposals for our core data systems. You will help ensure a seamless flow between microservices, our data lake, and downstream analytics. - Modern Pipeline Development: Build and ship production-level data pipelines using PySpark and SQL. You will collaborate on establishing standards for idempotency, monitoring, and performance tuning. - Lakehouse Data Modeling: Implement robust data modeling patterns (Medallion architecture: Bronze/Silver/Gold). You will ensure our Lakehouse is not just a data dump, but a high-performance source of truth for both BI and ML. - Databricks & Lakehouse Evolution: Contribute to the continuous improvement of our Databricks environment, with a focus on Delta Lake optimization and robust governance via Unity Catalog. - Systems Evolution & Stability: Act as the steward of our production environment. You will lead the refactoring of legacy pipelines to improve observability, reduce technical debt, and ensure seamless data flow between our microservices and the Databricks Lakehouse. - Technical Influence: Work closely with the Director of Data to refine our technical roadmap. You will lead by example through deep-dive code reviews and by maintaining a high bar for technical documentation. - Reliability & Governance: Conduct comprehensive audits to identify system inefficiencies. You will share ownership of data quality, security, and privacy across the entire lifecycle of our datasets.

• Medir el éxito de infraestructuras críticas mediante el análisis de adopción de componentes y performance técnico. • Desarrollar modelos predictivos y de optimización para potenciar la eficiencia operativa y la toma de decisiones. • Liderar diseños experimentales e inferencia causal para validar hipótesis en flujos técnicos y de negocio. • Definir KPIs estratégicos y asegurar la calidad, trazabilidad y escalabilidad de los activos de datos. • Traducir desafíos técnicos complejos en soluciones analíticas junto a equipos de Producto e Ingeniería.