Data Engineering Manager, Machinify

• Degree in Computer Science, Engineering, or a related field
• 3+ years of combined technical leadership and engineering management experience, preferably in a startup, with a proven track record of managing data teams and delivering high-impact projects from concept to deployment
• 10+ years of experience in data engineering, including building and maintaining production pipelines and distributed computing frameworks
• Strong expertise in Python, Spark, SQL, and Airflow
• Hands-on experience in pipeline architecture, code review, and mentoring junior engineers
• Prior experience with customer data onboarding and standardizing non-canonical external data
• Deep understanding of distributed data processing, pipeline orchestration, and performance tuning
• Exceptional ability to manage priorities, communicate clearly, and work cross-functionally, with experience building and leading high-performing teams
• Demonstrated experience leading small teams, including performance management and career development
• Comfortable with ambiguity, taking initiative, thinking strategically, and executing methodically
• Ability to drive change, inspire distributed teams, and solve complex problems with a data-driven mindset
• Customer-oriented, ensuring work significantly advances product value and impact

Desirable

• As a Data Engineering Manager, you will lead a high-performing team responsible for transforming raw external and customer data into actionable, trusted datasets
• Your team’s work powers product decisions, ML models, operational dashboards, and client integrations
• You’ll combine hands-on technical expertise with people and project leadership, reviewing and designing production pipelines, mentoring engineers, and driving best practices
• You will also be a key cross-functional partner, collaborating with product managers, Server teams, Platform teams, UI teams, SMEs, account managers, analytics teams, ML/DS teams, and customer success to ensure data is accurate, reliable, and impactful
• This is a high-visibility role with both strategic and tactical impact — shaping data workflows, onboarding new customers, and scaling the team as the company grows
• Lead, mentor, and grow a high-performing team of Data Engineers, fostering technical excellence, collaboration, and career growth
• Own the design, review, and optimization of production pipelines, ensuring high performance, reliability, and maintainability
• Drive customer data onboarding projects, standardizing external feeds into canonical models
• Collaborate with senior leadership to define team priorities, project roadmaps, and data standards, translating objectives into actionable assignments for your team
• Lead sprint planning and work with cross-functional stakeholders to prioritize initiatives that improve customer metrics and product impact
• Partner closely with Product, ML, Analytics, Engineering, and Customer teams to translate business needs into effective data solutions
• Ensure high data quality, observability, and automated validations across all pipelines
• Contribute hands-on when necessary to architecture, code reviews, and pipeline design
• Identify and implement tools, templates, and best practices that improve team productivity and reduce duplication
• Build cross-functional relationships to advocate for data-driven decision-making and solve complex business problems
• Hire, mentor, and develop team members, fostering a culture of innovation, collaboration, and continuous improvement
• Communicate technical concepts and strategies effectively to both technical and non-technical stakeholders
• Measure team impact through metrics and KPIs, ensuring alignment with company goals