Senior Data Engineering Manager

Fidelity National Information Services-posted 3 months ago
Full-time • Senior
Saint Petersburg, FL
5,001-10,000 employees
Credit Intermediation and Related Activities
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Are you curious, motivated, and forward-thinking? At FIS you'll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun. We are seeking a highly skilled Senior Data Engineering Manager to lead our data engineering team within the Enterprise Data and AI team. This role is pivotal in developing scalable data and analytics solutions, implementing high-quality codebases, and collaborating with various teams to drive product innovation. The ideal candidate will have extensive experience with Azure, Fivetran, Snowflake, Databricks, and a strong understanding of data architectures within the FinTech industry.

  • Lead and manage a team of data engineers to design, develop, and maintain scalable data pipelines and platforms.
  • Architect and implement robust data solutions using Fivetran, Azure Data Services Snowflake, and Databricks.
  • Ensure data integrity, security, and governance across all data initiatives.
  • Collaborate closely with business partners, managers, and engineers to facilitate needs into technical solutions and drive product innovation.
  • Drive ETL/ELT best practices and optimize data pipelines for performance and cost efficiency.
  • Establish and enforce data engineering standards, including coding practices, documentation, and testing strategies.
  • Act as a subject matter expert on data and analytics topics, providing technical guidance to stakeholders and contributing to technical documentation and knowledge-sharing efforts.
  • 8+ years of experience in data engineering, with at least 3+ years in a leadership role.
  • Proven expertise in Azure Data Services, Snowflake, and Databricks.
  • Strong understanding of data modeling, ETL/ELT pipelines, and real-time data processing.
  • Experience in developing complex, high-performance analytics applications with a focus on user experience, performance, and scalability.
  • Familiarity with CI/CD, DevOps, and Infrastructure as Code (IaC) for data pipelines.
  • Excellent leadership, communication, and stakeholder management skills.
  • Experience with Kafka, Airflow, or other data orchestration tools.
  • Knowledge of machine learning workflows and MLOps.
  • Hands-on experience with PCI and data governance frameworks (GDPR, CCPA, etc.).
  • Certifications in Azure, Snowflake, or Databricks.
  • A competitive salary and benefits.
  • A multifaceted job with a high degree of responsibility and a broad spectrum of opportunities.
  • Varied and challenging work to help you grow your skillset.
  • A work environment built on collaboration, flexibility and respect.
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