Senior Data Engineer

Role Description

We are seeking a highly skilled and experienced Senior Data Engineer to lead the development and management of our data platform. This pivotal role will focus on supporting critical data needs and developing foundational data models that are essential for advancing our cross-border remittances business. You will leverage your expertise in data warehousing, transformation, and modeling to build robust and scalable data solutions. Your responsibilities will encompass the entire build and deployment lifecycle of data movement and transformation, including managing users, scaling compute resources, and ensuring the platform operates optimally and efficiently. A key focus will be on maintaining robust data governance, ensuring data is well-defined, searchable, and trusted across the entire organization.

What you'll own

• Data Modeling & Management:
  • Design, implement, and evolve data models for core datasets.
  • Collaborate with stakeholders to translate commercial objectives into trusted data outcomes.
  • Establish and enforce data governance policies to guarantee data quality, security, and compliance.
  • Implement and maintain data cataloging and metadata management solutions.
• Platform Operations & Optimization:
  • Manage all aspects of the build and deployment lifecycle for data movement and transformation processes.
  • Oversee user access and resource allocation for compute infrastructure.
  • Ensure effective use of platform tools and resources for efficient ETL/ELT processing.
  • Manage the costs associated with all data platform technologies.
• Technical Leadership & Innovation:
  • Provide technical leadership and mentorship to other data engineers.
  • Evaluate and integrate new data technologies and tools.

Qualifications

• At least 7 years of experience in data engineering, with a strong emphasis on developing data platforms, data modeling, and managing data assets.
• In-depth, hands-on experience with technologies for data ingestion, job orchestration, data warehousing, and reporting.
• Proven ability to design, implement, and manage robust ETL/ELT pipelines using various tools (e.g., Spark, dbt).
• Strong experience with cloud data platforms (e.g., AWS, GCP, Azure).
• Proficient in SQL and advanced programming in at least one language (e.g., Python, Scala, Java).
• Experience with workflow orchestration tools (e.g., Astronomer, Apache Airflow).
• Solid understanding and practical experience with data governance principles.
• Demonstrated ability to optimize data platform performance and manage compute resources efficiently.
• Excellent analytical and problem-solving skills with meticulous attention to detail.
• Strong communication and interpersonal skills.

Bonus Points

• Experience in the financial services or FinTech industry, specifically with cross-border payments.
• End-to-end experience building data platforms using industry-standard tools.
• Proficiency in data modeling tools and techniques (e.g. dbt).
• Familiarity with modern data lake formats such as Delta Lake and Iceberg.
• Experience with real-time data processing and streaming technologies (e.g. Flink, Epsio).
• Experience with infrastructure as code (e.g., Terraform).
• Familiarity with data observability and monitoring tools (e.g. Metaplane, Datadog).
• Proficiency in BI and data visualization tools; experience using Mode is preferred.
• Experience using Blackline or Autorek reconciliation software.

AI Literacy & Tools

• A genuine curiosity about AI and how it can be applied in your area of work.
• Practical experience using AI tools in a professional context.
• Strong AI literacy — an understanding of what AI assistants can and cannot do.
• Awareness of the ethical considerations and responsible use of AI in the workplace.
• Prior experience using Claude (Anthropic) is a nice-to-have but not essential.

Benefits

• Unlimited annual leave.
• Great healthcare benefits.
• Employee discounts.