Staff Data Engineer at Galileo Financial Technologies Mexico

, , Argentina -

Full Time

Start Date

Immediate

Expiry Date

29 Mar, 26

Salary

0.0

Posted On

29 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Warehousing, Snowflake, dbt, Apache Airflow, SQL, ETL, ELT, Python, Data Governance, Data Quality, Airtable, Apache Kafka, CI/CD, Infrastructure as Code, Financial Services, Mentoring

Industry

Financial Services

Description

Employee Applicant Privacy Notice Who we are: Welcoming, collaborative and having the opportunity to make an impact - is how our employees describe working here. Galileo is a financial technology company that provides innovative and revolutionary software products and services that power some of the world's largest Fintechs. We are the only payments innovator that applies tech and engineering capabilities to empower Fintechs and financial institutions to unleash their full creativity to achieve their most inspired goals. Galileo leads its industry with superior fraud detection, security, decision-making analytics and regulatory compliance functionality combined with customized, responsive and flexible programs to accelerate the success of all payments companies and solve tomorrow's payments challenges today. We hire energetic and creative employees while providing them the opportunity to excel in their careers and make a difference for our clients. Learn more about us and why we work here at https://www.galileo-ft.com/working-at-galileo. The role: As a Staff Data Engineer, Risk Engineering, you will be a pivotal, hands-on expert within our data team. Leveraging your extensive experience, you'll design, build, and maintain highly scalable and robust data solutions that directly support our independent risk management goals. This role demands deep expertise in modern data warehousing, data modeling, and end-to-end pipeline development, preferably in an AI applications context. You will be an expert in our core stack: Snowflake, dbt, Apache Airflow, SQL, and Airtable. You will preferably have experience working with data products and technologies in an AI applications context. You will be responsible for the design, build and develop of our data infrastructure. You will be expected to autonomously drive and own projects from inception to completion, proactively identifying and mitigating risks. Your strategic thinking and technical leadership will not only deliver high-impact solutions but also help shape the data strategy for the team and department. You will provide mentorship and technical guidance to other engineers, championing best practices and fostering a culture of technical excellence. What you’ll do: Drive the architecture and implementation of complex data solutions, collaborating with risk analysts and business stakeholders to translate advanced requirements into robust data models and pipelines. Design and build highly optimized data workflows on Snowflake, utilizing its advanced features for large-scale financial data processing, cost optimization, and performance tuning. Develop, manage, and optimize sophisticated ETL/ELT pipelines using dbt, Python, and Apache Airflow to ensure data integrity and address high-exposure risks within financial datasets. Integrate and manage data from various sources, including external data sources, into our core data platform, ensuring seamless and automated data flow for critical business applications. Design and configure workflows based in Airtable for complex orchestrations of tasks Drive the strategic evolution of our modern data platform, taking full ownership of its design, maintenance, and long-term direction. Establish and enforce advanced data governance and quality processes, acting as a primary point of contact for escalations related to data accuracy and compliance within the financial domain. Mentor and provide technical contributions to the team of data engineers, participating on best practices, complex problem-solving Conduct expert-level code reviews and champion data engineering best practices across the team. Proactively troubleshoot and resolve highly complex data pipeline issues, preempting negative cross-functional impact. What you’ll need: 6+ years of hands-on experience in a data engineering role, with a strong background in data warehousing and modern data stack architectures. Advanced Level of English (Mandatory) Demonstrated expertise in Snowflake, including deep knowledge of its architecture, advanced features, and performance optimization techniques for large datasets. Expert-level proficiency with dbt for complex data transformation, dependency management, and building production-grade data models. Advanced experience with Apache Airflow for orchestrating and managing mission-critical data workflows. Hands-on experience with streaming data platforms - Apache Kafka (preferred) Experience in building and maintaining CI/CD pipelines using tools like GitHub Actions, GitLab CI/CD Experience with Infrastructure as Code (IaC) using Terraform (preferred), CloudFormation, or Ansible. Familiarity with Airtable, specifically in configuring workflows, integrating it as a data source and automating data synchronization for business operations. Mastery of SQL for complex querying, data manipulation, and performance tuning. Experience in the banking or financial services industry is highly preferred, with a strong understanding of financial data models, compliance, and regulatory requirements. Advanced expertise in data governance, data cataloging, metadata management, and implementing robust data quality frameworks. Proven track record of providing technical leadership and mentoring other engineers. Nice to have: Familiarity with data observability tools and practices. Knowledge of other cloud-native data platforms (e.g., AWS, GCP) Galileo Financial Technologies provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law. The Company hires the best qualified candidate for the job, without regard to protected characteristics. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. New York applicants: Notice of Employee Rights Galileo is committed to an inclusive culture. As part of this commitment, Galileo offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com. Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time. Internal Employees If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

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Responsibilities

The Staff Data Engineer will design, build, and maintain scalable data solutions to support risk management goals. This role involves driving the architecture of complex data solutions and mentoring other engineers.