CloudGeometry · 2 days ago
Engineering Manager
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Responsibilities
Lead and develop a team of engineers, ranging from junior-level to highly experienced professionals.
Design and implement highly scalable, reliable, and performant data pipelines using Databricks.
Develop and maintain architectural blueprints and design documentation for data models and ETL processes.
Work closely with stakeholders to assist with data-related technical issues and support their data infrastructure needs.
Optimize data flow and collection for cross-functional teams.
Ensure adherence to data quality and security regulations.
Collaborate with development teams to integrate data systems and pipelines efficiently.
Drive effective engineering processes and policies.
Scale the team by recruiting candidates from diverse backgrounds.
Contribute to the growth and efficiency of our data operations.
Qualification
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Required
Bachelor's or Master's degree in Computer Science, Information Technology or equivalent practical experience
4+ years of experience leading a high-performing team of engineers
6+ years of professional experience in data engineering, designing and implementing data pipelines, and building data infrastructure
Proven experience as a Data Engineer, with extensive experience using Databricks and related tools (Apache Spark, Delta Lake, MLflow, etc.)
Strong analytic skills and the ability to work with large, complex data sets
Experience working with AWS/Azure/GCP services
Proven experience in data modeling, data warehousing, and working with large, complex data sets
Experience with AI/ML technologies and their integration into data pipelines
Solid understanding of software development methodologies and tools, with an agile mindset
Excellent communication and teamwork skills, with the ability to work effectively in a globally distributed team environment
Benefits
Remote work option
Co-working space financial coverage
Flexible working hours
B2B with multiple benefits
Workspace program: $2500 for work equipment
Performance financial incentives
Paid courses and certifications (e.g., AWS, CKA, ML)
Participation in international conferences (e.g., CNCF Summits, KubeCon)