• You will develop and maintain data models and structures that enable efficient querying and analysis; • You will design, develop, and maintain data pipelines to transform and process large volumes of data from various sources, while adding business context and semantics to the data; • You will implement automated data quality checks to guarantee data quality and consistency across the whole data life cycle. • Live the mission: inspire and empower others by genuinely caring for your own wellbeing and your colleagues. Bring wellbeing to the forefront of work, and create a supportive environment where everyone feels comfortable taking care of themselves, taking time off, and finding work-life balance.

• Define and evolve the data architecture on Databricks • Design and implement scalable, high-performance data pipelines • Ensure engineering best practices, governance, security, and observability • Optimize pipelines, clusters, and cloud costs • Support production troubleshooting and drive technical improvements • Serve as a technical reference for the team and the client

• Collaborate with the team to define goals and deliver custom data solutions. • Innovate with new tools to improve infrastructure and processes. • Design and implement ETL processes, optimize queries, and automate pipelines. • Own projects end-to-end, working directly with clients. • Mentor and support team members, helping them deepen their knowledge in Data Engineering and model design. • Lead data pipeline development and guide technical decisions. • Act as a liaison between the team and stakeholders, ensuring alignment. • Foster team autonomy while ensuring smooth collaboration. • Contribute to technical research and stay ahead of solutions for future projects. • Focus on code quality—review, document, test, and integrate CI/CD. • Participate in candidate interviews and evaluations to help Mutt grow.

• Collaborate with the team to define goals and deliver custom data solutions. • Innovate with new tools to improve Mutt Data's infrastructure and processes. • Design and implement ETL processes, optimize queries, and automate pipelines. • Own projects end-to-end—build, maintain, and improve data systems while working with clients. • Develop tools for the team and assist in tech migrations and model design. • Build scalable, high-performance data architectures. • Focus on code quality—review, document, test, and integrate CI/CD.