Engineering Manager, Data Platform & ML Ops

📋 Description Lead and mentor a team of engineers across data platforms and ML operations. Own reliability, scalability, and continuous improvement of internal data infrastructure. Oversee the ML lifecycle including experimentation, training pipelines, deployment, and monitoring. Provide architectural guidance and help teams make strong engineering decisions. Collaborate with data scientists, product managers, and analysts to drive measurable outcomes. Establish standards and best practices across data engineering and ML operations. 🎯 Requirements 2+ years managing engineering teams focused on data platforms, ML, or related tech. 5+ years of professional experience in data, ML, or software engineering roles, preferably in SaaS. Strong understanding of data infrastructure and ML systems with ability to provide technical Experience leading multi-disciplinary teams and delivering reliable data products. Proven ability to drive technical change in fast-growing orgs. Familiarity with ClickHouse, Databricks, Snowflake, or BigQuery; ML lifecycle tools for training 🎁 Benefits Remote-friendly environment with location flexibility. Competitive compensation aligned with experience. Opportunity to work on advanced data and ML systems at scale. Lead and grow a talented engineering team while shaping technology strategy. Exposure to modern data platforms, ML operations, and cloud infra. Inclusive culture and ongoing professional growth opportunities.