Data Engineering Team Lead
vor 4 Wochen
Hopmann Marketing Analytics GmbH is a boutique consultancy for digital analytics, data engineering, and data science based in Munich-Neuhausen. Our team is passionate about making data accessible to everyone in meaningful visualizations, ad hoc reports, and sophisticated analyses.
We are looking for a proactive Data Engineering Team Lead to understand and communicate our company's vision, seamlessly integrate it into daily operations, and focus on the continuous development and success of the data engineering team in achieving strategic goals.
Key Responsibilities- Lead by example, with 80-90% of your time focused on hands-on data engineering tasks to drive the execution of projects, and the remaining 10-20% dedicated to mentoring, team leadership, and strategic alignment.
- Mentor and inspire a data engineering team of up to 6 employees, fostering a collaborative environment that encourages innovation, accountability, and continuous professional development.
- Understand the company's strategic objectives and translate them into actionable tasks to effectively communicate and integrate them into the team's daily operations to ensure alignment and drive results.
- Consult with clients to gather, understand, and analyze their unique requirements and objectives, to develop technical solutions that align with their strategic goals.
- Plan, execute, and deliver key data engineering projects, ensuring they meet timelines, budget constraints, and quality standards.
- Cooperate closely with your colleagues from the Data Visualization, Digital Analytics, and Data Science teams to develop innovative solutions.
- Identify emerging technologies and trends in the data engineering landscape and recommend strategies for adoption, to maintain our competitive edge and enhance our data engineering expertise.
- Contribute to business development to attract new clients and expand existing relationships, by demonstrating the compelling value and innovative capabilities of our data engineering solutions.
- Master's or higher in Computer Science, Data Science, Engineering, or related fields.
- At least 5 years of experience in data engineering with demonstrated ability to design, build, and maintain scalable and robust data pipelines.
- Deep understanding of data integration, data modeling, workflow orchestration, and CI/CD, and corresponding tools/technologies (e.g. SQL, Python, Spark, Airflow, Git).
- Proficiency in cloud services (AWS, Azure, GCP) and managed data services (like Snowflake, Databricks, dbt Cloud, MWAA).
- Familiarity with optimizing data systems and infrastructures in areas like performance, scalability, and stability, but also data quality, data observability, and data security.
- Experience with leading a data engineering team or managing complex data projects, including budgeting and timeline creation.
- Excellent communication and presentation skills in German and English, capable of clearly articulating complex data concepts to non-technical stakeholders.
- Leadership personality with convincing professional competence.
- Exciting, varied projects with well-known customers from various industries right from the start.
- Personal responsibility and involvement in strategic development.
- An open working atmosphere and flat hierarchies with competent colleagues.
- Further training and certifications, as well as participation in events and conferences.
- Flexible working, either hybrid or on-site in our state-of-the-art offices in Munich or at Schliersee.
We are looking for a Team Lead Data Engineering (m/f/d) to join our team with immediate effect.
We are passionate, committed, and goal-oriented, able to organize ourselves well, present ourselves confidently to our customers, and drive the entire company forward as a team.
We look forward to receiving your application with your earliest start date and salary expectations.
The salary range is €, depending on skills, qualifications, and experience.
Hopmann Marketing Analytics ist eine inhabergeführte Boutique-Beratung für Digital Analytics, Data Engineering und Datenvisualisierung.
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