Full Stack Software Engineer (Data Infrastructure)
What are you looking for in your next company? An open, friendly culture? Smart application of an excellent tech stack? Real diversity? Rock-solid products? If these matter to you, we have some great things to talk about!
Hearsay Systems is looking for a talented Full Stack Software Engineer to join our amazing Budapest team!
The Data Infrastructure team is responsible for providing and operating a flexible, resilient, efficient platform for reporting and analytics based on various internal and external data sources, from managing data pipelines to embedding reports into our products. You'll be working in a startup culture at one of Silicon Valley’s leading enterprise companies; working side by side with engineers that have years of experience designing and scaling extremely large systems.
If this sounds intriguing to you, then read on and apply!
Hearsay Data & Analytics empowers advisors and agents, administrators, and corporate executives to understand and continuously improve client engagement. Data is a key driver of measuring and growing value for both the enterprises we serve and their agents and advisors who engage with clients directly. Analytics allow us to measure the efficacy of client engagement behaviours in driving outcomes at all levels of financial services organisations, making every agent and advisor more effective, and increasing client satisfaction. Automated decisioning and human effectiveness powered by data-driven insights will become more and more a part of how the financial services will serve customers. Our Data & Analytics team covers the gamut of our approach and strategy for collecting, understanding, and acting upon data and the insights derived from it, from data exploration to advanced analytics technologies.
Who is Hearsay?
Hearsay Systems is transforming how bankers, advisors, and insurance agents acquire and service customers in an increasingly digital and regulated environment. Founded in 2009 by Clara Shih and Steve Garrity, and helmed by CEO Mike Boese, Hearsay Systems leads the field in offering sophisticated client engagement products to companies within the financial services vertical. We are a tightly knit and dedicated group that passionately believes in our products, our people, and our culture. Our products engage customers across Facebook, LinkedIn, Twitter, and Instagram, email, text, and voice. And every product syncs beautifully to Salesforce, Microsoft Dynamics, and other CRM systems.
Hearsay is used by more than 170,000 financial advisors and insurance agents. Our clients include Morgan Stanley, Goldman Sachs, Wells Fargo, JP Morgan Chase, Prudential, New York Life and Allstate. We enable them to get a real-time pulse of field conversations and to trigger more effective targeted advisor-client outreach with AI-optimized calls, text messages, email follow-ups, and social media interactions.
About the role:
- Working in a distributed team (in Budapest and San Francisco) of data and software engineers
- Solving hard challenges around providing a reliable and performant data platform - consisting of ETL/ELT data pipelines, data lake and data warehouse - that handles over 10 billion rows across hundreds of tables
- Working across Hearsay's web based products, adding and improving the ways users can interact with analytical data, reports and dashboards
- Focusing on quality, ensuring that we can provide our clients data that is clear and that they can trust
- Collaborating across a large part of the organization, with:
- 3+ years of software development experience
- Good understanding of HTML/CSS and related technologies
- Strong foundation with one modern applications language, ideally Python but Ruby, Kotlin, modern Java, C# and Go are all also acceptable
- Strong command of SQL
- Understanding of data flows between systems on networks and basic security constructs that are used in on-premise and cloud based enterprise solutions
- Desire to learn new technologies and ability to learn quickly
- Strong analytical and problem-solving skills
- Interest in learning about data engineering
- Ability to communicate in English (speaking, reading, and writing)