We are seeking a Principal Data Engineer (full-time) to join our data engineering team Berlin.
As a dynamic, forward-thinking organization, we are seeking an experienced Principal Data Engineer to lead our data engineering initiatives. This pivotal role requires a blend of technical prowess and leadership skills, ideally suited for a professional passionate about shaping the future of data engineering. The successful candidate will drive the development and optimization of our data architecture, ensuring our data systems are robust, scalable, and efficient.
You will:
- Advanced Data Architecture Design: Design and implement scalable and reliable data architectures. Lead initiatives for data modeling, data warehousing, and data lake development, ensuring the architecture supports current and future business needs. Develop and maintain scalable, efficient data architectures, incorporating modern data stacks like AWS, Databricks, and Snowflake. Ensure these architectures support both current and future business analytics, AI, and machine learning initiatives
- Advanced Data Engineering: Apply expertise in big data technologies, real-time data processing, and cloud-based systems to enhance our data capabilities. Implement data pipelines, ETL processes, and data storage solutions
- Expertise in ML/AI Tooling: Utilize tools such as AWS SageMaker, Databricks MLflow, and other advanced ML/AI technologies to facilitate data processing and analysis. Implement and oversee machine learning pipelines and data science workflows
- Team Mentorship and Collaboration: Act as a mentor to junior data engineers, fostering a culture of technical excellence. Collaborate with cross-functional teams, including data scientists, analysts, and IT professionals, to align data engineering efforts with organizational goals
- Innovative Solutions and Best Practices: Stay at the forefront of data engineering trends. Introduce innovative solutions and best practices in data processing, storage, and analytics. Evaluate and recommend new technologies to enhance our data capabilities
- Data Quality and Governance: Establish and maintain high standards for data quality and integrity. Implement data governance frameworks and ensure compliance with data privacy and security regulations
- Performance Optimization: Monitor system performance, identify bottlenecks, and implement solutions to optimize data flow and storage
You are:
- Experience: 8+ years of experience in data engineering with a demonstrated track record in designing and managing large-scale data systems. Experience in leading data engineering teams is essential
- Technical Expertise: Proficiency in big data technologies (e.g., Hadoop, Spark), database management systems (e.g., SQL, NoSQL), cloud services (e.g., AWS, Azure, GCP), and programming languages (e.g., Python, Scala, Java). Advanced skills in AWS, Databricks, Snowflake, and other modern data tools. Experience with big data technologies, real-time data processing, and cloud-based systems
- Leadership Skills: Strong leadership and team-building capabilities. Ability to mentor and develop technical teams
- Problem-Solving: Exceptional problem-solving skills and the ability to work on complex systems and challenges
- Communication: Excellent communication and interpersonal skills, with the ability to engage effectively with technical and non-technical stakeholders
You have:
- Strong programming skills in Python and SQL
- Knowledge of distributed systems and Spark distributed data processing engine
- Experience with ETL tools and pipelines that support data ingestion, processing, storage, and delivery, such as Airflow
- Understanding of data security and privacy regulations and how to ensure data quality, consistency, and accessibility
- Proficiency in designing, building, and maintaining data warehousing solutions based on Snowflake and Databricks Lakehouse Platform
- Expert understanding of dimensional data modeling techniques
- Data governance and management skills, such as defining and enforcing data quality standards, data contracts, data lineage, and data access policies, as well as ensuring data security and compliance
- Expert knowledge of AWS platform and cloud computing principles
- Strong infrastructure management skills, such as provisioning, configuring, and maintaining data servers, clusters, and networks, as well as automating and optimizing data workflows and processes
- Ability to design, plan, drive, and document major architectural changes and propose innovative solutions for data engineering problems
Some perks of becoming a Babbelonian:
- Enjoy 30 vacation days and the chance to take a 3-month Sabbatical. Plus family and life situation counseling.
- Decide how, when and from where you want to work with our flexible working hours and remote friendly options as Jobbatical (up to 3 months inside the EU) or work from our fully equipped office with nap, faith and family rooms.
- Learn and grow with the internal learning opportunities, and use a yearly learning & development budget for external training. Learn languages with Babbel for free with your full access to Babbel & Babbel Live classes.
- Take advantage of your mobility benefits options and a discounted Urban Sports Club membership.
- Be part of our employee communities (such as Femgineers, DE&I Ambassadors and LGBTQIA groups), attend cultural and regular social events.
Diversity at Babbel
As part of our ongoing journey towards building a diverse, equitable and inclusive company, we welcome everyone to apply, especially those individuals who are underrepresented in tech. We are a learning company, inside and out, and we encourage you to apply even if you do not fit all the technical requirements - all candidates are assessed based on skills, qualifications and on our business needs. Please state your pronouns in your application, and let us know if you’d like to be addressed by a name other than the one appearing on your official documents. If you have a disability or special need, feel welcome to inform us, so that we can provide you with the proper assistance in the application process.
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