Big Data Cloud Chapter Lead - Engineering Manager at ING BANK NV
Amsterdam, Noord-Holland, Netherlands -
Full Time


Start Date

Immediate

Expiry Date

25 May, 25

Salary

0.0

Posted On

25 Feb, 25

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

Are you a seasoned and eager Engineer, who loves Data and have managerial experience? Please read on!
We are looking for an ambitious colleague who can make our cutting-edge Cloudera stacks even better for our ING Private Cloud users while being a CL for the engineers working on Big Data Cloud.
Job description
Working at Cloud, area Data Services means working in a dynamic and challenging IT environment. With high ambitions, we deliver Big Data stacks based on Cloudera software to several ING departments across the organization. We ensure that the stack is secure, packed with new features and thoroughly tested before handover. Next to that, we help new consumers on their first steps in the Analytics landscape and onboard their use cases.
We are looking for a Chapter Lead/Engineering manager to guide, coach, and support our team of Big Data Cloud engineers. As Chapter Lead, you will be responsible for developing individual expertise within your chapter, fostering best practices, hiring and staffing and collaborating closely with cross-functional squads to ensure high-quality delivery. You will balance technical leadership with hands-on mentoring, shaping the direction of your chapter while supporting members in their career growth.
The ideal CL is someone with empathy, can create a safe environment for everyone, knows how to adjust communication so any message can be brought with respect, gets motivated by making also others successful and is curious and connect topics and people within the area.
Key Responsibilities (Managerial)
Chapter Leadership : Build, coach, and inspire a team of Big Data Cloud engineers. Promote a culture of continuous learning, experimentation, and innovation within the chapter of engineers with different technological backgrounds
Technical Excellence : Set and maintain standards for best practices, tools, and methodologies in [specific chapter field]. Drive initiatives to improve technical quality, scalability, and maintainability
Talent Development : Conduct regular one-on-one meetings, performance reviews, and growth plans with chapter members. Identify individual strengths and support members in their career paths
Community Building : Foster a strong sense of community within the chapter by organizing knowledge-sharing sessions, workshops, and other opportunities for professional development
Stakeholder Engagement : Engage with stakeholders across engineering, product, and business functions to ensure alignment on product goals, priorities, and strategies with those of your Chapter members
Communication : You can explain complicated subjects clearly to different audience
Environment shaping : You are friendly, empathetic and approachable and can challenge engineers in and out of your chapter
Curiosity : You are motivated to keep up to date with the latest developments and to introduce them to the team and projects where applicable
The CL part will be approx. 60% of your time; the other 40% will be hands-on contribution on Big Data Cloud ’s projects , helping develop the data-driven products.
Key Responsibilities ( Big Data Cloud )
The Big Data Cloud squad is looking for a data-driven engineer with experience on Apache Hadoop, Hive, Spark, Apache Knox, and similar technologies who loves to automate and has a natural tendency to help (and a little bit support) other engineering teams.

Responsibilities

Improve the current stack in our Ansible automation scripts
Investigate bugs and security findings and make them available via automated patching for running Big Data clusters.
Update and build Azure DevOps pipelines to make our lives, plus the lives of our consumers, easier.
Work on a future offering, where we transform our IPC BigData offerings from stacks to managed services.
Who are you

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