Position: Data Engineer
Category: Data Engineer
Experience: 4 years | English: fluent

-- 4 years of hands-on experience in developing, implementing and maintaining data pipelines, DWHs and databases, and backend architecture, preferably in Azure.
-- Working in Norwegian oil industry.
-- Dr. rer-nat. in Particle Physics from Heidelberg University.
-- Member of the ATLAS collaboration at CERN
-- Working with data at the Large Hadron Collider.
-- Publications in top peer-reviewed physics journals.
Data Engineer
Dr. rer. nat. in Physics

10 years of experience in science and 4+ years in IT as DE/DS 

-- Ciklum (Dec 2020 - present)
Develop and implement pipelines to ingest, process, validate and visualise data about estimated product deliveries and online sales for large brewery company

- Data pipelines using Azure Data Factory, Databricks and Synapse
- Ingestion of raw data from external sources on a daily basis with environmental tracking and failure recovery
- Data validation using Great Expectations Python-based tool
- Data stored in Delta tables and Synapse views
Tools and technologies: Azure, Python, Azure Databricks, DevOps

Project for audio book selling company
 - Azure data processing platform for a company selling audio books.
 - ETL pipelines to load sales data from different sources into Azure environment. Data processing, model features calculation and data ingestion into Azure ML predictive model.
 - Backend architecture for the client’s web and CRM applications
- Tracking and notification system to monitor all data workflows 
Tools and technologies: Python, SQL, Azure, Hubspot, Git

-- Infopulse/Cognite AS (Jan 2020 - Dec 2020)
Modelling project for the oil and gas reservoirs in North Sea for Norwegian oil company:
- Pipelines to process mining data from offshore oil fields (oil/gas/water fractions, pressure, sensor measurements, etc.). Generation of historical time series.
- Data processing from oil reservoir simulations. Generation of simulation time series.
- Dashboard visualisation of time series in Power BI for petroleum engineers.
Tools and technologies: Python, Spark, Databricks, Python SDK, Cognite Data Fusion, Docker, Power BI, REST API, Git

-- The Ad Masters, 11.2019-12.2019 
Python based A/B testing framework for the online selling platform

-- Ph.D. at Heidelberg University/ATLAS experiment, CERN, 05.2014 - 03.2019
- Statistical data analysis to identify potential dark matter candidates from particle collision data collected with the ATLAS detector
- Interpretation of the final search results. Studies of different models of dark matter production based on observed data. 
 - Implementation of parallel processing of large collision data sets on Linux based clusters
- Publications in peer-reviewed physics journals such as Physical Review Letters and Journal of High Energy Physics

Technologies & Tools:
-- Statistical data analysis, Bayesian methods, Python, C++, Bash, Linux, Git, SVN
-- Cutting edge technologies: machine learning, applied sectors (physics, biology, biophysics, healthcare, education), finance, energy industry, etc.
-- Close collaboration with international companies
-- Remote work and flexible working hours