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DataOps Engineering Manager (m/f/d)

Redcare Pharmacy

Skills

Required

  • Data Engineering / DataOps / platform engineering
  • Azure Databricks
  • Azure Data Factory ADF
  • Apache Kafka
  • CI/CD
  • automated testing
  • monitoring
  • logging
  • error handling
  • data ingestion pipelines
  • performance optimization

Preferred

  • ADF
  • Kafka
  • data ingestion frameworks
  • code reviews
  • DevOps

Are you an experienced engineering leader who enjoys developing people as much as building great technology? As our DataOps Engineering Manager, you'll lead a team of 5+ engineers while remaining actively involved in hands-on engineering, shaping our data ingestion capabilities and contributing directly to the solutions your team delivers. This role offers a unique opportunity to combine people leadership, hands-on technical ownership, and stakeholder management, giving you the freedom to drive DataOps initiatives independently while making a tangible impact on our data platform.

Our DataOps environment is built around Azure Databricks, Azure Data Factory (ADF), and Apache Kafka for event streaming first, enabling scalable batch and event-driven data ingestion solutions within Microsoft Azure. We embrace CI/CD automation, automated framework testing, monitoring, logging, error handling, and solution optimization to build robust, scalable, and maintainable data pipelines.

About Redcare Pharmacy

About Redcare Pharmacy: As Europe’s No.1 e-pharmacy Redcare Pharmacy is powered by passionate teams and cutting-edge innovation. We strive to create a healthy collaborative work environment where every employee feels valued and inspired to contribute to our vision “Until every human has their health”. If you’re seeking a career that offers purpose and aligns with your values join us and start your #Redcareer today.

Responsibilities

  • Lead, coach, and develop your team: Take ownership of the people leadership of 5+ DataOps Engineers, supporting their professional growth through regular one-on-ones, mentoring, performance management, and career development.
  • You'll foster a culture of accountability, technical excellence, and continuous learning while creating an environment where engineers can thrive.
  • Stay hands-on and build alongside your team: Actively contribute to the design, development, testing, and optimization of data ingestion frameworks and production-grade pipelines using Azure Databricks, ADF, and Kafka.
  • You'll write code, solve complex engineering challenges, participate in code reviews, and lead by example, maintaining strong technical involvement alongside your management responsibilities.
  • Own the DataOps strategy and engineering roadmap: Independently drive DataOps initiatives, define technical priorities, and guide the evolution of our ingestion frameworks.
  • You'll introduce and strengthen DevOps practices within Data Engineering, including CI/CD, automated testing, monitoring, logging, and error handling, while balancing delivery commitments with long-term platform scalability and reliability.
  • Collaborate closely with Data Architects, engineering leaders, product teams, and business stakeholders to translate requirements into scalable technical solutions.
  • You'll align priorities, manage expectations, communicate progress and risks, and ensure engineering initiatives support broader business objectives.
  • Take an active role in improving pipeline performance, reliability, observability, and cost efficiency.
  • You'll help establish engineering standards, address technical debt, troubleshoot production challenges, and encourage your team to continuously improve the quality and maintainability of our data solutions.

Requirements

  • People leadership experience: You have proven experience managing and developing engineering teams of 5+ people, ideally within Data Engineering, DataOps, or platform engineering.
  • You enjoy mentoring engineers, providing meaningful feedback, managing performance, and building a collaborative, high-performing team.
  • You have extensive practical experience designing, developing, and maintaining data ingestion pipelines using Azure Databricks, Azure Data Factory (ADF), and Apache Kafka.
  • You're comfortable writing production-ready code, implementing ingestion frameworks, troubleshooting complex pipelines, and contributing directly to engineering deliverables.
  • You have strong knowledge of CI/CD, automated testing, monitoring, logging, error handling, and performance optimization.
  • You have experience working with Data Architects, engineering teams, and business stakeholders to translate requirements into technical solutions.
  • You can independently drive complex initiatives, manage competing priorities, make sound architectural decisions, and communicate technical trade-offs clearly.
  • You enjoy being both a people manager and an active engineer.
  • You know when to empower your team and when to get directly involved in solving technical challenges.
  • You value knowledge sharing, constructive feedback, and building reliable solutions together rather than managing engineering solely from a distance.

Benefits

  • In order to provide you with the best possible support for your individual needs - whether it‘s living a healthy life, having enough time for your family, or developing your skills - we offer a wide range of different, site-specific benefits: Work from Home: If your job does not require you to be present in the office, we can arrange the place you work from individually - even for up to 20 days a year anywhere in the EU.
  • Grow!
  • We support and encourage your individual development through various in- and external trainings.
  • 30 days paid vacation per annum (plus another day on Rosenmontag) and the option to take unpaid vacation of up to 10 days (after one year working with us).
  • Stay healthy.
  • Profit from a membership (M) package at Urban Sports Club, so that you can take advantage of a huge variety of sport offers.
  • We promote teambuilding through creative team events, and celebrate our successes together at regularly scheduled parties.