
10,000+ employees
💸 Finance
💰 Post-IPO Debt on 2023-03
Insurance • Finance • Reinsurance
Swiss Re is a leading global reinsurance company that provides insurance-based risk transfer solutions. With a commitment to innovation and financial stability, Swiss Re helps clients navigate various risks, including life, health, and property. The company aims to enhance the sustainability and resilience of societies by offering reinsurance, insurance, and related services, ensuring businesses can thrive amid uncertainties.
🕒 March 4
Improve your chances of getting an interview by checking your resume score before you apply.

10,000+ employees
💸 Finance
💰 Post-IPO Debt on 2023-03
Insurance • Finance • Reinsurance
Swiss Re is a leading global reinsurance company that provides insurance-based risk transfer solutions. With a commitment to innovation and financial stability, Swiss Re helps clients navigate various risks, including life, health, and property. The company aims to enhance the sustainability and resilience of societies by offering reinsurance, insurance, and related services, ensuring businesses can thrive amid uncertainties.
• Collaborate closely with stakeholders to understand business questions and clearly specify key metrics and acceptance criteria for reporting solutions • Build and maintain the core data backbone by integrating multiple Finance data systems using PySpark and tools within the Palantir Foundry environment • Develop comprehensive data and reporting solutions that address business requirements for the wider Finance organization • Implement testing strategies to ensure deliverables meet specifications, including system performance and report timeliness • Ensure smooth operation of existing reporting platforms through structured change management activities • Participate in ad-hoc projects and work collaboratively with team members to address evolving business needs • Stay informed about the latest trends and best practices in data engineering and financial data analysis
• 5-9 years of working experience in data engineering and reporting • Proficiency in PySpark for data processing and management • Experience with Palantir Foundry & its applications (building pipeline using code-repository, creating data-health Checks & Expectations, data analysis in Contour) is an advantage. • Knowledge of Spark and optimizing spark-based pipelines • Ability to convert business problems into technical implementations • University degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Engineering, or Information Technology) • Excellent command of spoken and written English with ability to present to senior management.
• Flexible working arrangements • Professional development opportunities
Apply Now🕒 March 4
1001 - 5000
🤖 Artificial Intelligence
🔒 Cybersecurity
Data Architect responsible for designing scalable data architectures on AWS at AI & Data Engineering in Bangalore, India. Involve in developing data pipelines and managing data flows within AWS environments.
Amazon Redshift
AWS
Cloud
DynamoDB
ETL
Scala
Spark
🕒 March 2
1001 - 5000
🤖 Artificial Intelligence
🔒 Cybersecurity
Senior Data Engineer role at AI & Data Engineering focused on Databricks engineering.
🕒 February 24
5001 - 10000
🤝 B2B
🏢 Enterprise
💸 Finance
Data Engineering Manager leading design and delivery of data infrastructure at Huron. Collaborating with teams across Financial Services, Manufacturing, and Energy.
Airflow
Apache
ETL
PySpark
Python
SQL
Vault
🕒 February 23
1001 - 5000
🤖 Artificial Intelligence
🔒 Cybersecurity
Data Architect leading enterprise architecture strategy and implementing solutions in data management. Collaborating with stakeholders and teams for integration and data quality standards implementation.
Azure
ETL
Python
Spark
SQL
🕒 February 8
51 - 200
🎯 Recruiter
👥 HR Tech
🤝 B2B
Sr. Data Engineer designing and maintaining data pipelines in IT Services company located in Bangalore. Leading data engineering teams ensuring data management and infrastructure best practices.
Apache
AWS
Azure
Cloud
Java
Python
Scala
Spark
SQL