Strong experience with Infrastructure as Code using Terraform, including deployment, configuration, and management of Azure and Databricks resources.
Experience with event-driven architectures and streaming technologies, including Kafka, Azure Event Hubs, Event Grid, Apache Flink, or similar.
Experience with DBT and modern data transformation frameworks.
Experience with Data Vault 2.0 modeling methodologies.
Qualification wording
Strong experience with Infrastructure as Code using Terraform, including deployment, configuration, and management of Azure and Databricks resources.
Experience with event-driven architectures and streaming technologies, including Kafka, Azure Event Hubs, Event Grid, Apache Flink, or similar.
Experience with DBT and modern data transformation frameworks.
Experience with Data Vault 2.0 modeling methodologies.
Education & alternatives
Professional and Technical
- Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, or a related technical field; or equivalent training and professional experience.
- 5+ years of experience designing and implementing data engineering solutions and enterprise-scale data platforms.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Python
Scala
SQL
Azure
Databricks
dbt
Delta Lake
Kafka
Spark
Terraform
PySpark
Where the posting names them
- 5+ years of experience building ETL/ELT pipelines, data warehouses, and modern data platform architectures.
- 5+ years of experience developing and maintaining data applications and services using Python, Scala, or similar languages.
- 5+ years of hands-on SQL experience, including performance optimization, data analysis, and troubleshooting.
- 5+ years of experience developing and maintaining data applications and services using Python, Scala, or similar languages.
- 5+ years of hands-on SQL experience, including performance optimization, data analysis, and troubleshooting.
- 3+ years of experience with cloud data technologies, preferably Databricks on Azure.
- 3+ years of experience with cloud data technologies, preferably Databricks on Azure.
- Strong hands-on experience building and optimizing large-scale data processing solutions using Databricks and Apache Spark (PySpark, Spark SQL, Structured Streaming, Delta Lake).
- Experience working with structured, semi-structured, and unstructured data across a variety of data stores, including data warehouses, relational databases, object storage, and distributed data platforms.
- 5+ years of hands-on SQL experience, including performance optimization, data analysis, and troubleshooting.
- 3+ years of experience with cloud data technologies, preferably Databricks on Azure.
- Strong hands-on experience building and optimizing large-scale data processing solutions using Databricks and Apache Spark (PySpark, Spark SQL, Structured Streaming, Delta Lake).
Preferred Qualifications
- Strong experience with Infrastructure as Code using Terraform, including deployment, configuration, and management of Azure and Databricks resources.
- Experience with event-driven architectures and streaming technologies, including Kafka, Azure Event Hubs, Event Grid, Apache Flink, or similar.
- Strong experience with Infrastructure as Code using Terraform, including deployment, configuration, and management of Azure and Databricks resources.
- Experience with event-driven architectures and streaming technologies, including Kafka, Azure Event Hubs, Event Grid, Apache Flink, or similar.
- Experience with DBT and modern data transformation frameworks.
- Experience with event-driven architectures and streaming technologies, including Kafka, Azure Event Hubs, Event Grid, Apache Flink, or similar.
- Experience with DBT and modern data transformation frameworks.
- Experience with Data Vault 2.0 modeling methodologies.
Complete your application on juliusbaer.wd3.myworkdayjobs.com. The employer’s form will show what is required.
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth. Let’s shape the future of wealth management together.
At Julius Baer, we celebrate and value the individual qualities the candidates bring, enabling them to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth.
Our Global Products Solution (GPS) Technology department aims to strategically develop, strengthen and align the software engineering expertise and implement state of the art platforms covering Execution, Sales and Trading.
YOUR CHALLENGE
In our team, you will be a key contributor to building our Data Platform as a foundation for Data Analytics and AI. Your responsibilities will include:
Design, develop, and maintain scalable data pipelines, data products, and backend services supporting real-time decisioning, reporting, analytics, and AI use cases.
Design and implement data models for analytical and operational workloads, ensuring performance, scalability, and maintainability.
Produce high-quality, secure, testable, and maintainable code following engineering best practices.
Develop and maintain data governance, data quality, and monitoring solutions across the platform.
Collaborate with cloud, security, and architecture teams to ensure compliance with enterprise standards and cloud best practices.
YOUR PROFILE
Professional and Technical
Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, or a related technical field; or equivalent training and professional experience.
5+ years of experience designing and implementing data engineering solutions and enterprise-scale data platforms.
5+ years of experience building ETL/ELT pipelines, data warehouses, and modern data platform architectures.
5+ years of experience developing and maintaining data applications and services using Python, Scala, or similar languages.
5+ years of hands-on SQL experience, including performance optimization, data analysis, and troubleshooting.
3+ years of experience with cloud data technologies, preferably Databricks on Azure.
Strong hands-on experience building and optimizing large-scale data processing solutions using Databricks and Apache Spark (PySpark, Spark SQL, Structured Streaming, Delta Lake).
Experience working with structured, semi-structured, and unstructured data across a variety of data stores, including data warehouses, relational databases, object storage, and distributed data platforms.
Solid understanding of data modelling principles.
Experience implementing CI/CD pipelines and automated deployment practices.
Strong design, implementation, and testing skills.
Excellent communication and collaboration skills, with experience working in Agile delivery environments.
Preferred Qualifications
Strong experience with Infrastructure as Code using Terraform, including deployment, configuration, and management of Azure and Databricks resources.
Experience with event-driven architectures and streaming technologies, including Kafka, Azure Event Hubs, Event Grid, Apache Flink, or similar.
Experience with DBT and modern data transformation frameworks.
Experience with Data Vault 2.0 modeling methodologies.
Ability to provide technical leadership and guide architectural and engineering decisions.
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