Data Project Engineer
Location: Vienna, Austria
Department: Data Solutions / Engineering
Employment Type: Full-time
Company Overview
We are a leading technology and innovation-driven company, specializing in data-centric solutions for a diverse range of industries. Our Vienna office serves as a hub for advanced data projects, where we transform raw data into actionable insights and scalable systems. We pride ourselves on fostering a collaborative and forward-thinking environment, where creativity and technical excellence converge to solve complex challenges.
Position Summary
We are seeking a skilled and motivated Data Project Engineer to join our dynamic team in Vienna. In this role, you will be responsible for designing, implementing, and managing end-to-end data pipelines and infrastructure. You will collaborate closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to deliver robust data solutions that drive decision-making and operational efficiency. The ideal candidate possesses strong technical expertise, a problem-solving mindset, and the ability to manage projects from conception to deployment.
Key Responsibilities
- Design and Development:
- Architect, build, and maintain scalable and reliable data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
- Develop ETL/ELT processes and workflows to ensure data quality, consistency, and accessibility.
- Implement data storage solutions, including data warehouses, data lakes, and databases, optimizing for performance and cost.
- Project Management:
- Lead and oversee data engineering projects from requirements gathering to delivery, ensuring alignment with business objectives and timelines.
- Coordinate with internal and external stakeholders to define project scope, milestones, and success metrics.
- Monitor project progress, identify risks, and implement mitigation strategies to ensure timely and successful completion.
- Collaboration and Support:
- Work closely with data scientists and analysts to understand data requirements and provide clean, reliable datasets for analysis and modeling.
- Partner with IT and DevOps teams to deploy and maintain data infrastructure in cloud and on-premises environments.
- Provide technical guidance and mentorship to junior team members, fostering a culture of continuous learning and improvement.
- Innovation and Optimization:
- Evaluate and integrate new tools, technologies, and best practices to enhance data engineering capabilities.
- Optimize existing data processes for improved performance, scalability, and reliability.
- Ensure data security, privacy, and compliance with relevant regulations (e.g., GDPR).
Qualifications and Skills
Essential:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
- Proven experience (3+ years) in data engineering, with a strong portfolio of successful data pipeline projects.
- Proficiency in programming languages such as Python, SQL, Java, or Scala.
- Hands-on experience with big data technologies (e.g., Apache Spark, Hadoop, Kafka) and cloud platforms (e.g., AWS, Azure, GCP).
- Expertise in database design, data modeling, and working with relational and NoSQL databases.
- Familiarity with data orchestration tools (e.g., Airflow, Luigi) and version control systems (e.g., Git).
- Strong project management skills, with the ability to manage multiple priorities in a fast-paced environment.
- Excellent problem-solving abilities and attention to detail.
- Fluent in English; German language skills are a plus.
Desirable:
- Certifications in cloud technologies or data engineering.
- Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
- Knowledge of machine learning pipelines and MLOps practices.
- Understanding of data visualization tools and dashboards (e.g., Tableau, Power BI).
