Insurance Data Team: Analytics, ML & Architecture

GRiT Solutions; Lisboa; Híbrido; EUR 40 000 - 60 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Continuous Training and Certifications

GRiT Prizes (Birthday Prize, etc.)

Exclusive Partnerships/Discounts

Unique Events

Welcoming Office Amenities

Competitive Compensation

Pay for Performance

Resumo da oferta

GRiT Solutions in Lisbon is expanding its data team for a long-term project in the insurance sector. We're seeking various data profiles including Data Engineers, Analysts, and ML Engineers. Candidates should have relevant skills in data management, analytics, and tools such as Snowflake and Python. English fluency is critical, and experience in regulated environments is desirable. The position offers a hybrid/remote working model, continuous training, and competitive compensation.

Qualificações

• Experience in data engineering, analytics, or related roles is essential.
• Ability to work effectively in a team, particularly in a client-facing situation.
• Knowledge of insurance or banking regulations is an advantage.

Responsabilidades

• Develop and manage data pipelines and workflows.
• Conduct data analysis to provide insights and support decision making.
• Lead and oversee various data projects ensuring quality and governance.

Conhecimentos

Data Engineer skills (ELT/ETL, orchestration, data quality)

Data Analytics skills

ML Ops

Fluent in English

Experience in regulated environments

Ferramentas

Snowflake

Talend

Dataiku

Qlik

Apache Airflow

Python

Descrição da oferta de emprego

GRiT Solutions in Lisbon is expanding its data team for a long-term project in the insurance sector. We're seeking various data profiles including Data Engineers, Analysts, and ML Engineers. Candidates should have relevant skills in data management, analytics, and tools such as Snowflake and Python. English fluency is critical, and experience in regulated environments is desirable. The position offers a hybrid/remote working model, continuous training, and competitive compensation.