Lead Data Engineer

Are you passionate about transforming complex financial data into actionable insights? Join our dynamic team where you'll lead the design and implementation of sophisticated data pipelines that power critical business decisions. This is your opportunity to shape the future of financial analytics while working with cutting-edge technologies in a collaborative environment.

About the Role

As a Lead Data Engineer, you'll be at the forefront of our data innovation efforts, architecting robust data solutions that deliver meaningful impact across our finance organization. You'll collaborate with cross-functional teams to translate business requirements into scalable, efficient data systems.

Key Responsibilities

Design and develop sophisticated data pipelines and ETL processes to support financial reporting and analytics needs Lead technical implementation of data solutions using modern technologies and best practices

Optimize data models and query performance to ensure efficient data processing and retrieval Lead and mentor data engineering team members, fostering technical growth and knowledge sharing

Collaborate closely with business stakeholders, Product Owners, and business analysts to understand requirements and align technical solutions with business objectives

Partner with a global development team to design and implement comprehensive solutions Deliver high-performance data solutions leveraging PySpark, Python, and enterprise data platforms

Implement data quality frameworks to ensure accuracy and reliability of financial data Drive innovation by researching and implementing new data technologies and methodologies

Troubleshoot and resolve complex data issues across various systems and platforms Document technical processes, architectures, and solutions for knowledge sharing

About the Team

The Finance Reporting & Analytics Engineering team is responsible for designing and implementing complex data pipelines and analytics solutions that support key decision-making business processes across the finance organization. Our team takes pride in delivering high- quality data solutions that provide valuable insights to drive strategic financial decisions and operational excellence.

About You

You're a problem-solver at heart with a passion for data and technology. You thrive in collaborative environments where you can apply your technical expertise to solve real business challenges. Your strong communication skills enable you to bridge the gap between technical concepts and business needs, making complex data solutions accessible to all stakeholders.

We are looking for candidates who meet these requirements:

9+ years of experience in data engineering or related roles

Good SQL skills for data analysis

Hands-on experience with Python and PySpark for data processing and transformation

Experience working with modern analytics platforms like Palantir Foundry, Databricks, or Snowflake

Proven track record of designing and implementing scalable data pipelines

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or related field (or equivalent practical experience)

These are additional nice to haves:

Knowledge of TypeScript for front-end data visualization applications Experience with Git and version control workflows

Familiarity with financial data and reporting requirements Experience with cloud-based data platforms (AWS, Azure, or GCP)

Knowledge of data governance and compliance requirements in financial contexts Experience with agile development methodologies

About Swiss Re

Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. We cover both Property & Casualty and Life & Health. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 15,000 employees across the world.

Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.

If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience.

We may use AI-powered tools to support the review and evaluation of applications for this position. These tools provide additional insights to our recruitment teams, but all hiring decisions are carefully reviewed and made by people. To learn more about how we use AI in recruitment and how we handle your personal data, please review our Data Privacy Statement before applying.

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Reference Code: 137871

Job Segment: Data Analyst, Data

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