Data Engineer (Databricks)

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.