Data Engineering Manager

ONCH

Zürich

On-site

CHF 180,000 - 240,000

Full time

14 days+

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Job summary

ON.com LLC is seeking an Engineering Manager for the Data Enablement team in Zürich, leading data engineers, analysts and scientists to deliver impactful data products for Commercial (Digital, Retail and B2B). You will design data models, bring in new sources, build pipelines and ensure clean, tested, documented data while guiding architecture and governance.

You will mentor the team, align with stakeholders, drive data strategy, and champion best practices across the cloud environment (GCP)

Qualifications

  • 8+ years of experience in data warehousing, data modeling and ELT.
  • Proficient in SQL and Python.
  • Strong commercial domain experience with e.g. Ecommerce, Retail or Sales.
  • Experience managing one or more IC teams.
  • Cloud and platform fluency with cloud environments, APIs, data pipelines, observability and CI/CD (GCP preferred).
  • Familiar with AI tooling for data and applying AI to data solutions.
  • Excellent collaborative communication and stakeholder influence.

Responsibilities

  • Lead data engineering, data science, and analytics teams to deliver data products.
  • Partner with cross-functional stakeholders to translate business needs into robust data models.
  • Define data architecture, governance and best practices.
  • Drive data strategy and ensure security and compliance.
  • Mentor and develop team members.

Skills

Data warehousing
Data modeling
ELT concepts
SQL
Python
Cloud platforms
AI tooling
Stakeholder influence

Tools

GCP

Job description

In shortAs the Engineering Manager of the Data Enablement team for the Commercial function (Digital, Retail and B2B) you will be responsible for driving the design of data models, bringing in new data sources and building data pipelines, while leveraging SQL to provide clean, tested, documented and well-defined data.You will act as a leader for data engineers, data analysts and data scientists by providing guidance on architectural and design decisions, while evangelizing and encouraging our best practices and governance policies.Lastly you will act as a point of contact for multiple business functions and collaborate with the stakeholders to create relevant data products to enhance data adoption at On and to increase trust.Meet the TeamThe data enablement team is responsible for building, maintaining and growing internal data products that empower everyone at On to impact business outcomes by making informed decisions.You will be overseeing a team of data engineers who take care of the company’s data needs for Commercial (Digital, Retail and B2B). You will be leading a small focused team of data engineers, closely working with the data platform engineers, other data engineers, data analysts, data scientists and stakeholders to deliver valuable data products for the company.You will be part of a talented and diverse function of data engineers, data scientists and data governance experts who are passionate about revolutionizing how we leverage data to solve complex challenges across On. As a data leader, you will play a critical role in shaping our data strategy and driving execution of data initiatives.Your MissionYour primary objectives as an Data Enablement Engineering Manager are:Drive Strategic Alignment & Business Impact: Partner with cross-functional stakeholders to understand business requirements, and proactively identify and deliver data products that have a significant impact on stakeholders across functions or regions.Lead Decisive Execution: Enable the team to make timely and informed decisions for consequential, potentially irreversible decisions, and provide direction/support to others in tackling complex, new problems by identifying underlying issues and root causes.Provide Technical Leadership: Be accountable for your team's technical decisions and solutions, ensuring they align with Data Engineering best practices and On overall Tech's architecture north star, security, and compliance guidelines.Champion Team & Talent Development: Actively promote formal and informal mentoring, provide growth opportunities to your team, and build an inclusive team environment that fosters a culture of seeking out and delivering candid feedback.Your StoryYou are a proven data engineering expert and leader ready to manage a data engineering team, accountable for technical delivery, quality, and hiring in the Data Engineering space. You should be able to demonstrate:Deep Data Proficiency: 8+ years of related experience or equivalent, with deep technical expertise in data warehousing, data modeling and ELT concepts, and are experienced in SQL, Python or equivalent programming.Commercial Domain Expertise: You possess significant experience partnering with Commercial stakeholders in e.g. Ecom, Retail or Sales, translating complex business needs into robust data solutions and high-quality data models. This expertise spans knowledge of social media and digital marketing data sources, POS and customer data platforms, EDI systems, data science models like MMM and CLV, and providing customer insights through data-driven insights.Proven People Leadership: Proven experience in managing one or more teams with Individual Contributors (ICs) under direct management. You possess the ability to empower your team to ship high-quality code at pace, helping them navigate trade-offs between perfect and 'production-ready.Cloud & Platform Fluency: Expert knowledge of data infrastructure, APIs, data pipelines, observability and workflow orchestration in distributed cloud environments, with hands-on experience on cloud platforms (GCP preferred) and automated CI/CD.AI savvy: Proven familiarity with AI tooling for data such as Analytics LLMs/conversational analytics and demonstrable knowledge of using AI to innovate in the data sphere.Collaborative Influence: You are an exceptional communicator and a genuine team player, adept at guiding team decisions, fostering consensus through professional influence, and effectively conveying complex technical information to diverse audiences.
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