2 дня назад
Engineering Manager (DWH Data Tools)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Engineering Manager (DWH Data Tools) (Python/Node/Go): Managing and evolving data ecosystem tools including Superset, Jupyter Hub, and DataHub while developing internal BI and data-exploration solutions with an accent on engineering leadership, data-platform architecture, and service reliability. Focus on leading engineers, translating user pain points into technical designs, maintaining DWH tools under SRE processes, and balancing shifting priorities.
Location: Worldwide; remote work available. Flexible work is also available from company offices. Relocation support is offered to hubs in Cyprus, Serbia, Spain, or Georgia.
Company
, formerly Different Technologies, develops fintech products and supporting data platforms.
What you will do
- Lead, mentor, and manage the DWH Data Tools engineering team, including performance management, 1-on-1s, hiring, and professional development.
- Oversee the evolution and maintenance of Superset, Jupyter Hub, and DataHub.
- Lead the architecture, design, and implementation of internal BI, data-exploration, and other custom data tools.
- Collaborate with product stakeholders, data engineers, analysts, and other teams to translate user pain points into technical solutions.
- Drive team planning and delivery while managing flexible deadlines and changing business priorities.
- Ensure reliability, stability, service maintenance, and incident control in line with SRE processes.
Requirements
- At least 1 year of experience managing engineering teams in a fast-paced environment.
- Strong technical expertise with Python and experience with Go or Node.js.
- Experience designing, deploying, and managing data tools such as BI platforms, data notebooks, or data catalogs.
- Experience with hiring, team development, performance management, delivery management, and cross-functional collaboration.
- Ability to plan flexibly, prioritize effectively, and work amid ambiguity and changing requirements.
- English at B1 level or higher is required for communication with an international team.
Nice to have
- Experience implementing or maintaining services alongside SRE processes.
- Experience in data warehousing, banking, or fintech.
- Familiarity with Superset, Jupyter Hub, or DataHub internals.
- Experience with Apache Kafka, Airflow, DBT, Kubernetes, Snowflake, or Lake House architectures.
Culture & Benefits
- Remote or office-based work with flexible arrangements.
- Relocation assistance for employees and their families.
- Healthcare coverage, paid sick leave, and 20 days of annual leave.
- Education budget for language lessons, professional training, and certifications.
- Wellness budget supporting mental health and fitness activities.
- Collaborative environment focused on innovation, transparent feedback, and recognition of achievements.
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