Data Warehouse/BI Engineer

Under the operational responsibility of the Solution Owner, you are responsible to work with Databricks and SQL Server databases, both relational and multidimensional, in compliance with the SCOR policies and procedures that produce high-quality software products and services. Right from prototyping and designing functional code to coding and testing, you collaborate with the US Life business and technical stakeholders and take ownership of the software until it is handed over to the end users.

You are fully integrated within the Data Chapter, you contribute to develop the community, define and share guidelines, best practices, experience with others and perform technological watch on your domain.

You will join the Tech, Data and AI department (more than 200 employees across the globe) and will be able to grow and evolve in a global and very dynamic structure providing products, services, and support to all SCOR Group worldwide.

As a leading global reinsurer, SCOR offers its clients a diversified and innovative range of reinsurance and insurance solutions and services to control and manage risk. Applying "The Art & Science of Risk," SCOR uses its industry-recognized expertise and cutting-edge financial solutions to serve its clients and contribute to the welfare and resilience of society in around 160 countries worldwide.

Working at SCOR means engaging with some of the best minds in the industry - actuaries, data scientists, underwriters, risk modelers, engineers, and many others - as we work together to find solutions to pressing challenges facing societies.

As an international company, our common culture is defined by "The SCOR Way." Serving both to build momentum that drives the Group forward and as a compass to guide our actions and choices, The SCOR Way is anchored by five core values, reflecting the input of employees at all levels of the Group. We care about clients, people, and societies. We perform with integrity. We act with courage. We encourage open minds. And we thrive through collaboration.

SCOR supports inclusion and the diversity of talents, and all positions are open to people with disabilities.

• BS in Computer Science or related degree or equivalent work experience required
• 3+ years of working with Databricks, the medallion architecture, Databricks SQL, PySpark, Delta tables, pipelines and parquet files, focused on building and operating ETL/ELT workloads.
• 3+ years of experience building, enhancing, and supporting large-scale Enterprise ETL processes (data integration, migration, and data quality verification), including Python scripting for automation/reconciliation, with a proven track record of successful deliveries.
• Strong Python skills for ETL development (scripting, data processing, and automation), including writing reusable modules, implementing logging/error handling, and integrating with scheduling/orchestration.
• Experience working with data platforms enabling AI solutions.
• Experience/ Knowledge of the Reinsurance business and/or the financial services industry is a plus

You may not meet every requirement listed in the job description. If you bring broad expertise and alignment to the role and resonate with our core values, we encourage you to apply.

Relocation assistance within the U.S. is available for this position. Candidates must have valid authorization to work in the U.S. without the need for employer sponsorship now or in the future.

Hybrid Work Policy:

SCOR is committed to an "in-office" culture where people can collaborate, exchange ideas, and establish stronger working relationships while ll providing flexibility. To support employee work-life balance and increase opportunities for employees to excel every day, SCOR operates with a hybrid working arrangement. SCOR employees work 3 days per week in an office with the flexibility to work 2 days per week remotely.

At SCOR, we CARE about clients, people, and societies, and we are committed to placing them at the center of everything we do. Providing great benefit choices to you and your family is just one of the ways we support the physical, financial, and emotional well-being of the people who make our company successful - you.

Benefits We Offer

• Medical, vision, and dental coverage
• 401(k) Plan with a competitive match
• Company-funded Defined Contribution Retirement Program
• Life and AD&D insurance
• Long- and Short-Term Disability
• Flexible Parental Leave
• Unlimited Sick Days
• Volunteer Time
• Summer Fridays
• Learning & Development Resources
• Personal Wellness Tools and Rewards
• Competitively priced gym memberships from a large nationwide network of gym brands and local fitness studios
• And More!

Pay Range for roles performed in KC & CLT: $107,000-$130,500 base salary per year. Actual salaries may vary based on various factors including

but not limited to location, experience, role and performance. The range listed is just one component of SCOR''s total compensation package for employees. Other rewards may include annual bonuses, short- and long term incentives. In addition, we provide a variety of benefits to employees, including health insurance

coverage, life and disability insurance, a retirement saving plan, paid holidays and paid time off.

• On software development:

• Design, build, and optimize end-to-end ETL/ELT pipelines (batch and incremental loads) in Databricks to ingest, transform, and load enterprise data into the lakehouse/data warehouse.

• Develop, test, and maintain ETL code (PySpark and Python scripts, Databricks notebooks/jobs, and SQL) and implement logging, error handling, and monitoring for reliable daily operations.

• Identify and evaluate opportunities to integrate artificial intelligence(AI) and predictive analytics into existing data and BI workflows.

• Partner with business and data stakeholders to identify source systems, define data mappings/business rules, and document transformations and lineage for ETL processes. o Write, maintain, test, and document ETL components (Databricks notebooks/jobs, Python scripts, SQL procedures, and SSIS packages) including unit tests, reconciliation checks, and data quality rules.

• Collaborate with product owners, solution owners, QA, and other engineers to deliver ETL enhancements end-to-end (requirements, build, test, deploy), and support releases into production.

• Apply agile delivery practices to ETL work, including backlog refinement, sprint planning, and disciplined testing (data validation, reconciliation, and performance testing).

• Participate in code reviews and CI/CD for ETL assets (Python/PySpark, SQL, and Databricks jobs) to ensure maintainability, security, and operational stability.

• Create and maintain Python scripts to automate data ingestion, file handling, and operational tasks (e.g., parameterization, re-runs, alerts), and to generate data quality/reconciliation reports.

• On software maintenance/Business As Usual support

• Provide ongoing maintenance, support and enhancements in existing systems and global reporting platforms: troubleshoot and fix software defects, performance issues, and software compatibility problems.

• Provide production support to systems that host PII data, responding quickly to any production issues that arise.

• Maintain documentation and version control of software code and related artifacts

• Implement software security best practices and adhere to industry standards and regulations.

• On innovation

• Stay up-to-date with emerging trends, technologies, and software engineering best practices.

• Provide recommendations for continuous improvement.

• Work alongside other engineers on the team to elevate technology and consistently apply best practices.

• Leverage automation and AI tools to improve data quality, data processing and reporting efficiency.

• On software development:

• Design, build, and optimize end-to-end ETL/ELT pipelines (batch and incremental loads) in Databricks to ingest, transform, and load enterprise data into the lakehouse/data warehouse.

• Develop, test, and maintain ETL code (PySpark and Python scripts, Databricks notebooks/jobs, and SQL) and implement logging, error handling, and monitoring for reliable daily operations.

• Identify and evaluate opportunities to integrate artificial intelligence(AI) and predictive analytics into existing data and BI workflows.

• Partner with business and data stakeholders to identify source systems, define data mappings/business rules, and document transformations and lineage for ETL processes. o Write, maintain, test, and document ETL components (Databricks notebooks/jobs, Python scripts, SQL procedures, and SSIS packages) including unit tests, reconciliation checks, and data quality rules.

• Collaborate with product owners, solution owners, QA, and other engineers to deliver ETL enhancements end-to-end (requirements, build, test, deploy), and support releases into production.

• Apply agile delivery practices to ETL work, including backlog refinement, sprint planning, and disciplined testing (data validation, reconciliation, and performance testing).

• Participate in code reviews and CI/CD for ETL assets (Python/PySpark, SQL, and Databricks jobs) to ensure maintainability, security, and operational stability.

• Create and maintain Python scripts to automate data ingestion, file handling, and operational tasks (e.g., parameterization, re-runs, alerts), and to generate data quality/reconciliation reports.

• On software maintenance/Business As Usual support

• Provide ongoing maintenance, support and enhancements in existing systems and global reporting platforms: troubleshoot and fix software defects, performance issues, and software compatibility problems.

• Provide production support to systems that host PII data, responding quickly to any production issues that arise.

• Maintain documentation and version control of software code and related artifacts

• Implement software security best practices and adhere to industry standards and regulations.

• On innovation

• Stay up-to-date with emerging trends, technologies, and software engineering best practices.

• Provide recommendations for continuous improvement.

• Work alongside other engineers on the team to elevate technology and consistently apply best practices.

• Leverage automation and AI tools to improve data quality, data processing and reporting efficiency.