Data Engineer (Analytics)

Your Task

• Participating in data analytics projects from end to end in Microsoft Azure environment
• Build and maintain data pipelines (Azure Data Factory) 
• Implement data transformation logic using Apache Spark (Databricks, Synapse)
• Turning raw data into relevant datasets and insights
• Mentoring junior colleges
• Building highly scalable data products for the automated consolidation, process and analyse large amounts of data for machine learning - from conception to prototyping to operation, batch and streaming
• Evaluating the latest trends and technologies in data engineering and drive innovative solutions for data management in the machine learning context
• Contribute to ensuring continuous quality, reusability and performance improvement and take 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 (clean-code) and test-driven software development environment with a devops mindset
• In close cooperation with data scientists, you implement exciting AI use cases (e.g. entity extraction, recommender, chatbots) with data of all kinds (e.g. time series, images, documents)

Your Profile

• At least 3 years of relevant professional experience as Data Engineer
• 2+ years of experience with Python
• Hands-on software development skills
• Solid knowledge of SQL and coding skills in general
• Very good experience in object-oriented programming and application modularization
• Expertise in designing and implementing data models (principles, methods, best practices)
• Experience in implementation of different data integration frameworks: batch-oriented or sync/async real-time integration
• Demonstrated ability to understand and communicate technical details at all levels of the organization
• Experience in multiple forms of Data Storages (relational, analytical or in-memory databases, objects stores, search engines, graph databases) and their interrogation, physical data modelling
• Best-practice and implementation for continuous integration / delivery: Unit-testing, CICD Pipelines and deployment (preferably Azure DEVOPS, Gitlab)
• Ability to work in an independent, conscientious and solution-oriented way
• Fluency in English
• Teamplayer (agile team experience is a plus)

Nice to have:

• University degree in computer science, business informatics, mathematics or in a related field
• Experience with CRM/ERP source systems
• Experience with Continuous Integration/Continuous Delivery (CI/CD)
• Experience with clean-code, configurability and reusability
• Experience with Cloud technologies like Microsoft Azure or similar environment
• Development of serverless (Azure Data Factory, Synapse Analytics) or container-based applications (Kubernetes) provisioning and deployment
• Distributed processing frameworks: Spark-based data transformations (Databricks, Data Factory)
• Productionalising and publishing data services as scalable, performant Data APIs
• Experience in Pipeline Orchestration and Scheduling (ex: Airflow)
• Monitoring and logging (Elastic, Datadog), telemetry
• Technical development and integration of User-Request Workflows through reusable Rest APIs
• Experience in machine learning and deep learning algorithms productionalisation in Cloud
• Up to date with emerging technologies and trends in data engineering

Your ZEISS Recruiting Team: