Job description
Our client is seeking a Senior Data Engineer to lead the design, operation, and optimization of enterprise data platforms within the insurance sector. This role will oversee high‑availability pipelines, multi‑source ingestion, and advanced data quality frameworks, while ensuring compliance with regulatory requirements and internal policies. The successful candidate will play a key part in embedding AI‑driven solutions, enabling trusted datasets for analytics, and driving digital transformation across insurance operations.
Key Responsibilities
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL processes for structured and unstructured insurance data.
- Collaborate with actuaries, underwriters, and business analysts to translate insurance operations requirements into technical solutions.
- Optimize data warehouse and lakehouse architectures to support real-time analytics and machine learning models.
- Partner with cross-functional teams on digital transformation projects, including customer insights, claims automation, and risk modeling.
- Architect and maintain scalable ETL/ELT pipelines with scheduling, caching, partitioning, modelling, schema evolution, and lineage tracking to support both batch and real-time streaming.
- Partner with analytics and product teams to operationalize AI-driven data solutions across the insurance business.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or a related discipline.
- A minimum of 5 years of experience in data engineering, analytics engineering, or database management.
- Strong proficiency in SQL and Python for data manipulation and automation.
- Familiarity with cloud platforms (AWS or Azure) and modern data warehousing concepts.
- Hands-on with CI/CD (GitLab/Jenkins), Terraform, automation scripting.
- Proven experience in data pipeline development and maintenance.
- Strong expertise in distributed data processing and streaming architectures.
- Hands-on experience with Snowflake platform.
- Proficiency in Python programming for automation and data engineering tasks.
- Solid knowledge of SQL, data modeling, and ETL/ELT processes.
