Senior Data Analytics Engineer - FinTech
Role details
Job location
Tech stack
Job description
Our remote-first culture means you have the flexibility to work in your employing country wherever you feel the most focused and productive. This freedom comes with wonderful tailored, location-specific perks designed to support your whole life, not just your work. Think unlimited annual leave , great healthcare benefits, and employee discounts. We want you to thrive and focus entirely on making your biggest impact! In turn, we expect you to bring high ownership and commitment to your work. This is a place where we value trust and high performance, and we'll provide the environment and support needed for you to excel., We are seeking a highly skilled and experienced Data Analytics Engineer to join our dynamic team. This is a senior-level Individual Contributor (IC) role where you will operate with a high degree of independence. You will focus on supporting critical data needs and developing foundational data models that are essential for driving our cross-border remittances business forward. You will act as a technical lead on projects, leveraging your analytical and problem-solving skills to build robust and scalable data solutions., * Technical Project Management: Independently lead technical projects from conception to deployment. You will be responsible for defining timelines, managing resources, and ensuring the delivery of high-quality data solutions without constant supervision.
- Business Partnership: Collaborate with data analysts, and business stakeholders to translate commercial objectives into well-defined technical projects. You will act as a primary point of contact for partners, ensuring they have reliable self-serve data for strategic decision-making.
- Advanced Data Analytics: utilize Python and SQL to perform deep-dive analytics and build automated scripts. You will also utilize tools like Excel for rapid prototyping and business-facing reporting.
- Reconciliation & Financial Integrity: Oversee data reconciliation processes to ensure financial accuracy. (Experience with tools such as AutoRek or ReconArt is highly valued here).
- Tooling & Optimization: Lead the adoption of data transformation tools to empower teams in their data-driven decision-making processes.
Requirements
- Experience: Proven experience in analytics engineering, data engineering, or a similar role.
- Industry Experience: Proven experience in the financial services or FinTech industry, particularly with cross-border payments.
- Technical Skills: Proficiency in SQL and at least one programming language (e.g., Python) is required for data manipulation and scripting.
- Data Technologies: Hands-on experience with data warehouse technologies, specifically Databricks.
- Problem-Solving: Excellent analytical and problem-solving skills with strong attention to detail.
- Communication: Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders and partners., * Reconciliation Tools: Experience with AutoRek, ReconArt, or similar financial reconciliation software.
- BI & Visualization: Proficiency with business intelligence tools such as Tableau, PowerBI, or Looker.
- Cloud Infrastructure: Experience working within the AWS ecosystem.
AI Literacy & Tools As Zepz continues to build AI into how we work, we expect everyone to engage with it as a core part of their role. For this position we are looking for:
- A genuine curiosity about AI and how it can be applied in your area of work - from accelerating analysis and insight generation, to improving how we design and deliver processes and communications.
- Practical experience using AI tools in a professional context - whether to connect information, draft content, build frameworks, or create insights from data. We want people who actively use AI to increase productivity, not those who are waiting to be told to.
- Strong AI literacy - an understanding of what AI assistants can and cannot do, how to prompt effectively, and how to critically evaluate AI-generated output before using it.
- Awareness of the ethical considerations and responsible use of AI in the workplace, particularly in the context of sensitive data, customer experience, and compliance. Prior experience using Claude (Anthropic) is a nice-to-have but not essential - what matters most is that you are genuinely engaged with AI as a tool, comfortable experimenting, and eager to share what works with your wider team.