Engineering Manager - Python [DWH Data Tools]

We are looking for an experienced and driven Engineering Manager to manage our DWH Data Tools team. This team is responsible for managing and evolving our critical data ecosystem tools, including Superset, Jupyter Hub, and DataHub, while also developing new, in-house solutions - including internal BI and data-exploration tools - to fit specific business needs.
This role merges technical leadership with comprehensive team management. The ideal candidate will possess strong leadership skills and technical expertise across the team's stack - Python, plus Node.js and Go - along with a proven track record managing engineering teams and data platforms. You will be pivotal in planning, optimizing development processes, and translating product ideas into robust technical solutions that solve real user pain points - often while navigating shifting priorities and evolving business needs.
Challenges that await you:

• People Management: Lead, mentor, and manage a team of engineers. Take ownership of their performance, regular 1-on-1s, and continuous professional development

• Product Collaboration & Solution Brainstorming: Collaborate closely with product stakeholders to understand user pain points. Lead the brainstorming of technical solutions and translate product vision into actionable designs

• Planning & Execution: Drive planning activities for the team. Create and manage development plans, adeptly handling flexible deadlines and shifting business priorities

• Service Maintenance: Oversee service maintenance in strict alignment with SRE processes, taking responsibility for the reliability, stability, and incident control of the tools within the DWH

• Architecture & Development: Oversee the architecture, design, and implementation of data tools (Superset, Jupyter Hub, DataHub) and lead the development of custom solutions to meet new business requirements

• Stakeholder Communication: Manage communication with data engineers, analysts, and other stakeholders to ensure seamless data integration and tool usability

What makes you a great fit:

• 1+ years of experience managing engineering teams in fast-paced settings, preferably fintech with Python or Go stack

• Hiring, development, performance, and delivery management and strong skills in cross-functional collaboration and the ability to build partnerships

• Strong technical expertise in designing, deploying, and managing data tools (e.g., BI platforms, data notebooks, or data catalogs)

• Proven ability to manage flexible planning, balancing dynamic priorities and deadlines

• Excellent communication and collaboration skills, with the ability to partner effectively across teams and regions

• An adaptable, structured mindset — able to prioritize effectively and stay grounded amid ambiguity and change

• B1 or higher English level for effective communication with an international team

Your bonus skills:

• Experience implementing or maintaining services alongside SRE processes

• Work experience in DWH and/or the banking/fintech sphere

• Familiarity with the technical stacks or internals of Superset, Jupyter Hub, or DataHub

• Experience with data integration frameworks (e.g., Apache Kafka)

• Knowledge of ETL tools (e.g., Airflow, DBT)

• Experience with Kubernetes

• Experience with Snowflake or Lake House architectures

Our ways of working:

• Innovative Spirit: A commitment to creativity and groundbreaking solutions

• Honest Feedback: valuing open, transparent communication

• Supportive Team: a strong, collaborative community

• Celebrating Achievements: recognizing our wins together

• High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances

Our benefits:

• Relocation support to one of our hubs — Cyprus, Serbia, Spain or Georgia — with assistance for the employee and their family

• Flexible work from one of our offices or remote

• HealthcareCoverage

• Education Budget: Language lessons, professional training and certifications

• Wellness Budget: Mental health and fitness activity reimbursements

• Vacation policy: 20 days of annual leave and paid sick leave

Originally posted on Himalayas