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We are: Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact. With the right people and the right ideas, there’s no limit to what we can achieve Are you a fit? Sounds awesome, right? Now, let’s make sure you’re a good fit for the role: Key Responsibilities • Design, develop, and maintain scalable data pipelines using ETL/ELT processes. • Develop and implement data integration workflows to meet operational business needs. • Write robust scripts and complex SQL queries to extract, transform, and load data from multiple sources. • Design, optimize, and maintain data pipelines and architectures, ensuring data accessibility, cleanliness, and reliability. • Contribute to the design and implementation of data warehouse architectures and data lakes. • Support stream and batch data processing workflows. • Work with relational and non-relational databases, ensuring efficient design and optimization. • Apply data modeling techniques to support data consumption and analytics requirements. • Ensure data quality, consistency, and compliance with data governance and security practices. • Collaborate with software engineers and data consumers to align data integration workflows with business needs. • Apply version control and CI/CD principles to support reliable data development and deployment. Must-have Skills • At least 4 years of professional experience as a Data Engineer. • Proven experience designing, building, and maintaining scalable data pipelines and ETL/ELT processes. • Experience developing data integration workflows and working with multiple data sources. • Experience designing, optimizing, and maintaining data architectures and pipelines. • Experience with relational and non-relational database design and optimization. • Experience with data pipeline orchestration and workflow management. • Experience with cloud infrastructure and data security and governance best practices. • Advanced SQL. • Azure and Databricks. • Data processing using batch and stream processing paradigms. • Version control and CI/CD principles. • Data quality, consistency, and reliability practices. Nice-to-have: • AI Tooling Proficiency : Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows. What we offer: • A High-Impact Environment • Commitment to Professional Development • Flexible and Collaborative Culture • Global Opportunities • Vibrant Community • Total Rewards *Specific benefits are determined by the employment type and location. Find out more about our culture here .

Data Engineer (Databricks)

Don't apply unprepared

Data Engineer (Databricks)

Don't apply unprepared