(Senior) Data Engineer at Templafy in Copenhagen, NY
About you We would like to hear from you if you are a collaborator who takes initiative and has several years of experience working with data management solutions. This can include:
Building and optimizing pipelines for data ingestion and transformation using Delta Lake and Spark Schema design and dimensional data modeling of disconnected datasets Advanced SQL knowledge and experience working with relational databases Ensuring compliance with data privacy and information security regulations It is a plus if you have experience building Data Science applications, have Python skills or knowledge of data reporting tools such as Tableau and Power BI. Technologies we use Data Platform:
Azure Synapse Analytics, Azure Data Lake Storage, Delta Lake, Apache Spark, Python, Azure Purview Data Reporting:
Power BI, Excel, DAX Hosting:
100% Azure How we work Teams:
Each team consists of 4-6 engineers. Teams are cross-functional, self-organised and free to choose their own process, but most use a flavour of Scrum with a 2-week sprint. We believe in the lean principles - e.g. short feedback cycles, minimising handovers, and therefore each team has full responsibility for the features they own from development to deployment. Guilds:
Guilds are a place to share knowledge and experiences, and to get help and ideas from others. We currently have a DevOps, Cloud, Back-end, Front-end, Security, QA, and Tracking guild. Architecture:
We try hard to avoid over-engineering and always strive for the simplest solution possible. While we are in the early stages of building our data platform, our design process is guided by selecting simple technologies with a broad application spectrum rather than narrowly focussed ones. Test focused:
We like to test the code we build, and we have a continuous integration infrastructure in place that runs our tests on every push and notifies the team on Slack if something breaks. DevOps mindset:
We are cloud first, and everything is hosted in Microsoft Azure. Each team is responsible for deployments and monitoring of their own services. All work is managed through Azure DevOps including backlog management, source control, pull-requests, releases, and testing. Automation:
We like to automate as much as possible and constantly extend and improve our T-SQL based framework and infrastructure as code solution. Design:
We have a written coding standard, and we follow clean code principles. We develop most of our features using pair programming. Every change is peer-reviewed. We have tools for automatic code clean-up that ensure consistent formatting and structured and fail builds if any rule is violated. Tools:
We use some of the best tools available for the job including Microsoft Azure, Visual Studio 2019 Enterprise, Slack, Zoom, Git, Azure DevOps. Learning:
We believe in lifelong learning and encourage everyone to read books, go to conferences, take courses, and certifications. We want to invest in everyone's personal and professional development, and therefore we provide the necessary resources to support this. Every sprint we have internal Tech Talks and from time to time we also host and speak at meetups. Flexible:
We have distributed teams across offices in Copenhagen, Berlin and Eindhoven. Yet, all meetings and work happen online. This gives us freedom to work from home when you have a repair person coming, your child is sick, etc., and also enabled us to initiate the necessary measures within a minimal amount of time when COVID-19 hit the world.
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
Building and optimizing pipelines for data ingestion and transformation using Delta Lake and Spark Schema design and dimensional data modeling of disconnected datasets Advanced SQL knowledge and experience working with relational databases Ensuring compliance with data privacy and information security regulations It is a plus if you have experience building Data Science applications, have Python skills or knowledge of data reporting tools such as Tableau and Power BI. Technologies we use Data Platform:
Azure Synapse Analytics, Azure Data Lake Storage, Delta Lake, Apache Spark, Python, Azure Purview Data Reporting:
Power BI, Excel, DAX Hosting:
100% Azure How we work Teams:
Each team consists of 4-6 engineers. Teams are cross-functional, self-organised and free to choose their own process, but most use a flavour of Scrum with a 2-week sprint. We believe in the lean principles - e.g. short feedback cycles, minimising handovers, and therefore each team has full responsibility for the features they own from development to deployment. Guilds:
Guilds are a place to share knowledge and experiences, and to get help and ideas from others. We currently have a DevOps, Cloud, Back-end, Front-end, Security, QA, and Tracking guild. Architecture:
We try hard to avoid over-engineering and always strive for the simplest solution possible. While we are in the early stages of building our data platform, our design process is guided by selecting simple technologies with a broad application spectrum rather than narrowly focussed ones. Test focused:
We like to test the code we build, and we have a continuous integration infrastructure in place that runs our tests on every push and notifies the team on Slack if something breaks. DevOps mindset:
We are cloud first, and everything is hosted in Microsoft Azure. Each team is responsible for deployments and monitoring of their own services. All work is managed through Azure DevOps including backlog management, source control, pull-requests, releases, and testing. Automation:
We like to automate as much as possible and constantly extend and improve our T-SQL based framework and infrastructure as code solution. Design:
We have a written coding standard, and we follow clean code principles. We develop most of our features using pair programming. Every change is peer-reviewed. We have tools for automatic code clean-up that ensure consistent formatting and structured and fail builds if any rule is violated. Tools:
We use some of the best tools available for the job including Microsoft Azure, Visual Studio 2019 Enterprise, Slack, Zoom, Git, Azure DevOps. Learning:
We believe in lifelong learning and encourage everyone to read books, go to conferences, take courses, and certifications. We want to invest in everyone's personal and professional development, and therefore we provide the necessary resources to support this. Every sprint we have internal Tech Talks and from time to time we also host and speak at meetups. Flexible:
We have distributed teams across offices in Copenhagen, Berlin and Eindhoven. Yet, all meetings and work happen online. This gives us freedom to work from home when you have a repair person coming, your child is sick, etc., and also enabled us to initiate the necessary measures within a minimal amount of time when COVID-19 hit the world.
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine LearningEstimated Salary: $20 to $28 per hour based on qualifications.
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