

Search by job, company or skills

This job is no longer accepting applications
Your Position
You will work as a Data Engineer in the Predictive Maintenance team. This hybrid and multi-cultural team consist of Data scientists, Data Engineers, a DevOps engineer, a QA engineer, an Architect, an UX designer, a Scrum Master, and a Product Owner.
Through predictive solutions, the Digital Service Platform aims at optimizing customers assets usage and maintenance, impacting their performance, cost, and sustainability KPIs by expanding the lifetime of the components.
In your role, you will participate together with the other Data Engineers in solution design discussions led by our product architect, where your knowledge and input will be highly valued. You will collaboratively work with IT and business SMEs to ensure delivery of high-quality end-to-end data pipelines.
Your responsibilities
You will be developing, testing, and documenting the data (collection and processing) pipelines for Predictive Maintenance solutions. The data collection consists of (complex) data pipelines from (IoT) sensors and low/high level control components to our data platform. When the data is in the cloud, it must be processed and made available as data products to our data scientists
Align implementation efforts with other back-end developers across multiple development teams
You will develop scalable data pipelines to transform and aggregate data for business use, following software engineering best practices. For these data pipelines you will make use of the best frameworks available for data processing like Spark. We are continuously improving on the solutions we use and encourage you to keep challenging the status quo
You develop our data services for customer sites towards a product, using (test & deployment) automation, componentization, templates, and standardization to reduce delivery time of our projects for customers. The product provides insights into the performance of our material handling systems at customers all around the globe
You will contribute to the design, build, and improve a CI/CD pipeline, including (integration) test automation for data pipelines. In this process you strive for an ever-increasing degree of automation
.
Your Profile
· Minimum 5 years experience with building complex data pipelines and data solutions.
· Bachelor's or Master's degree in Computer Science, IT, or equivalent.
· Hands-on experience with data modeling
· Hands-on experience with programming in Java and Scala (python is a plus).
· Hands-on experience with Streaming processing (e.g., Spark) and Streaming and/or batch storage (e.g. Kafka, Oracle)
· Experience in building APIs
· Experience in data engineering using DevOps principles
· Experience in building highly performant and secure data pipelines
· Data Schema's (e.g., JSON/XML/Avro)
· Storage formats (e.g., Azure Blob, SQL, NoSQL)
· Deploying services as containers (e.g., Docker)
· Experience in building highly performant and secure data pipelines
· Knowledge and experience with MLOps (E2E Data and Machine Learning Pipelines)
· Working with cloud services (preferably with Azure and Databricks)
· Experience in data quality management and monitoring is a plus.
· Experience with Predictive Maintenance model development is a plus.
Job ID: 151638577
Skills:
snowflake , S3, Redshift, Jenkins, Lambda, Spark Streaming, Apache Kafka, Gitlab, Data Governance, Python, AWS, Alation, Glue, Data Quality Mesh
Skills:
.NET, data warehouses , Spark SQL, Power Bi, Azure Log Analytics, Powershell Scripting, Hive, Azure Data Factory, Data lakes, Microsoft Azure Data platform, Azure SQL Data Warehouse, Azure Storage Services, Azure Application Insights, Data Bricks, Stream Analytics, data marts, Event Hubs, Azure SQL DB, Azure Analysis Services
Skills:
S3, RDS, Pyspark, Databricks, Emr, Redshift, Python, Sql, AWS, Etl
Skills:
Java, Unix, Apache Flink, Data Modeling, Schema Design, Pyspark, Data Cleansing, Apache Spark, Data Warehouse Concepts, Shell Scripting, Sql, ELT, Apache Airflow, Linux, Apache Kafka, Restful Apis, Python, Etl, Data Transformation, Data Quality Validation
Skills:
proxmox , Servicenow, Kvm, Windows Server, Prometheus, Grafana, Datadog, Terraform, Vcenter, Python, AWS, Esxi, Vmware Vsphere, PowerShell, Bash, Jira, Ubuntu, Git, Nsx, Ansible, Rhel, Powercli, Vsan, networking fundamentals