Data Engineer (Analytics) Position at ZEISS Group
Your Task
Are you a skilled Data Engineer looking to work on exciting data analytics projects in a Microsoft Azure environment? Join ZEISS Group and take part in:
- Participating in end-to-end data analytics projects within Microsoft Azure.
- Building and maintaining data pipelines using Azure Data Factory.
- Implementing data transformation logic with Apache Spark (Databricks, Synapse).
- Transforming raw data into impactful datasets and insights.
- Mentoring junior colleagues.
- Developing highly scalable data products for automated data consolidation and analysis for machine learning purposes—from conception to operation.
- Evaluating and integrating the latest data engineering trends and technologies to foster innovative solutions.
- Ensuring continuous quality, reusability, and performance improvement while taking responsibility for applications and stakeholders during development, commissioning, and operation.
- Automating and deploying data transformations and pipelines on the provided Data Platform.
- Working in an accurate, test-driven software development environment with a devops mindset.
- Collaborating closely with data scientists to implement AI use cases such as entity extraction, recommenders, and chatbots using diverse data types (e.g., time series, images, documents).
Your Profile
To excel in this role, you should have:
- At least 3 years of relevant professional experience as a Data Engineer.
- 2+ years of hands-on experience with Python.
- Solid software development skills.
- Strong knowledge of SQL and general coding skills.
- Expertise in object-oriented programming and application modularization.
- Proficiency in designing and implementing data models following principles, methods, and best practices.
- Experience with different data integration frameworks, be it batch-oriented or sync/async real-time integration.
- Ability to understand and communicate technical details at all organizational levels.
- Experience with multiple types of data storages (relational, analytical, in-memory databases, object stores, search engines, graph databases) and their interrogation, physical data modeling.
- Best practices and implementation for continuous integration/delivery, including unit testing, CICD pipelines, and deployment (preferably with Azure DEVOPS, Gitlab).
- Independence, conscientiousness, and a solution-oriented work style.
- Fluency in English.
- A strong team player mentality (experience in agile teams is a plus).
Nice to Have
Additionally, the following skills are a plus:
- A university degree in computer science, business informatics, mathematics, or a related field.
- Experience with CRM/ERP source systems.
- Experience with clean-code, configurability, and reusability.
- Proficiency in cloud technologies like Microsoft Azure or similar environments.
- Experience developing serverless (Azure Data Factory, Synapse Analytics) or container-based applications (Kubernetes) for provisioning and deployment.
- Distributed processing frameworks experience, such as Spark-based data transformations using Databricks or Data Factory.
- Experience in productionalising and publishing scalable, performant Data APIs.
- Knowledge of pipeline orchestration and scheduling tools (e.g., Airflow).
- Monitoring, logging, and telemetry expertise (Elastic, Datadog).
- Experience in technical development and integration of user-request workflows through reusable REST APIs.
- Experience with machine learning and deep learning algorithms productionalisation in the cloud.
- Keeping up-to-date with emerging technologies and trends in data engineering.
Your ZEISS Recruiting Team
Bartók Tímea, Fedor Fanni, Hrehuss Orsolya, Kiss Bernadett, Meláth Laura, Sturcz Noémi, Sztaskó Daniella, Wenner Lili.
Join ZEISS Group as our new Data Engineer (Analytics) and be a part of our innovative and dynamic team!