Senior Data Engineer

February 13

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Logo of Wizeline

Wizeline

Wizeline is a global technology services provider specializing in digital transformation. The company offers a wide range of services including product engineering, cloud and DevOps, data and AI, and design to help companies achieve high-impact innovation. Wizeline's offerings aim to enhance operational efficiency, improve customer experiences, and accelerate business outcomes through cutting-edge AI and agile methodology. They serve a variety of industries, such as media and entertainment, financial services, and healthcare, providing tailored solutions to meet specific market needs. Their focus on AI technologies and human-centric experiences positions them at the forefront of technology-driven business evolution.

Ux Design • Product/Platform Development • Cloud & DevOps • Data • Artificial Intelligence

1001 - 5000 employees

Founded 2014

🏢 Enterprise

☁️ SaaS

🤖 Artificial Intelligence

💰 $43M Series B on 2018-03

📋 Description

• Wizeline is a global digital services company helping mid-size to Fortune 500 companies build, scale, and deliver high-quality digital products and services. • We thrive in solving our customer’s challenges through human-centered experiences, digital core modernization, and intelligence everywhere (AI/ML and data). • We help them succeed in building digital capabilities that bring technology to the core of their business. • Wizeline prioritizes a culture of diversity and development for its nearly 2,000 person team spread across the globe. • We believe great technology comes from a mix of talents and perspectives. • Our core values of ownership, innovation, community, and inclusivity are central to our work. • Wizeline is invested in its employees' growth, offering opportunities to create personalized career paths and develop in-demand skills. • We even have a free education program, Wizeline Academy, to help both employees and the broader community upskill in tech.

🎯 Requirements

• Proficiency in Python for data processing and analysis. • Experience with Databricks for large-scale data processing. • CI/CD pipelines, ideally using Azure DevOps. • Version control with Git. • Cloud computing, with a focus on Microsoft Azure. • SQL for database interactions and data transformations. • .NET (C#) development. • Experience with Azure Data Lake. • Kubernetes for container orchestration. • Monitoring and alerting systems. • Infrastructure as Code (e.g., Terraform). • Knowledge of financial or FinTech domains, particularly in regulatory reporting. • Adaptability and agility in a fast-paced, evolving business environment. • Strong knowledge and experience in identifying and resolving data quality issues. • Familiarity with various data domains in the financial industry is a plus.

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