09/14/2026 updated

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Senior Data Engineer

Solna, Sweden
Germany +3
info: Germany, Spain, Poland, Sweden
M.Sc. Machine Learning
Solna, Sweden
Germany +3
info: Germany, Spain, Poland, Sweden
M.Sc. Machine Learning

Profile attachments

Simon_Low_CV_2026.pdf

AI AgentsRAGGitHub CopilotGitHub ActionsdbtMLOpsLangChainApache AirflowCloud EngineeringData ArchitectureData GovernanceExtract Transform Load (ETL)Python (Programming Language)Machine LearningDataOpsAzure Machine LearningAzure Data LakeSQL DatabasesPulumiCloud Platform SystemSnowflakeGitData LakeKubernetesApache KafkaMachine Learning OperationsTerraformData PipelineDockerDatabricks
I've worked for scale-ups and startups including Klarna, DigiHaul (DHL Supply Chain), and Depict (Y-
Combinator) across the full data stack - cloud infrastructure, data pipelines, warehouses, AI/ML model training
and productionization.
In my current project at DigiHaul, I redesigned their data platform (Snowflake, DBT, Azure) to support real-time
analytics and cut data latency from hours to seconds across 150+ tables. Alongside this, I introduced data
governance across the platform (RBAC, lineage, etc.), rebuilt the DBT data model following dimensional
modeling best practices, and built a configuration-driven framework for data ingestion to integrate new data
sources without any code changes. In my previous roles I designed an MLOps platform at Klarna that reduced
time-to-market for new credit risk models from several weeks to days, and trained recommender systems at
Depict that boosted conversions for their e-commerce customers.
Recently, my work has moved more toward LLMs and agents: I built a Cortex AI chatbot for DigiHaul that lets
their team query their Snowflake data warehouse in plain English and get back charts and explanations, and
integrated AI coding tools across their data platform to raise code quality and speed up delivery.

Experience

Professional experience5 - 10 years
Freelancer since2021

Languages

GermanNative speakerEnglishNative speaker

Project history

Senior Data Engineer / Data Architect

DigiHaul (DHL Supply Chain)

Transport & Logistics

>10.000 team member


DigiHaul is a digital freight platform - backed by DHL and now part of DHL Supply Chain.
  • Realtime Analytics: Redesigned their complete data ingestion process, moving from batch ingestion to CDC streaming bringing end-to-end data latency from 24h down to under 60 seconds across 150+ tables.
  • Snowflake Data Warehouse Redesign: Improved their data model using dimensional modeling best practices together with DBT and Snowflake features like Dynamic Tables. Implemented role-based security and permission management across the entire data platform. Moved to a fully automated deployment process with infrastructure-as-code and GitOps.
  • Snowflake Cortex AI Chatbot: Built a text-to-SQL chatbot allowing their teams to query their warehouse by asking questions in plain English and get back detailed graphs and explanations.
  • ML & Data Applications: Designed and implemented cloud infrastructure in Azure to deploy multiple ML applications into production. This included components like batch jobs, data pipelines, dashboards, APIs, and web apps.
  • Databricks Platform: Set up their first Databricks environment as part of the transition to DHL Supply Chain, with scheduled daily DBT jobs handling the transformations. Github Actions deploy the full setup via Databricks Asset Bundles, validate DBT code, and generate documentation.
  • AI Tooling: Introduced AI coding tools across the data engineering team to improve quality and speed up delivery of new features.

AI Engineer

DepictAI AB

Internet & IT

10-50 team member


Depict is an AI-powered product discovery platform for e-commerce, backed by Y Combinator.
  • Recommender Systems: Extended the in-house ML pipeline and recommender framework to support personalized product recommendations in real time.
  • NLP & Clustering: Improved cross-sell recommendations using BERT, UMAP, and DBSCAN to identify product groups.
  • Customer Integrations: Supported customer calls as a forward-deployed engineer and integrated several online shops with the Depict platform.
Skills: AI Engineering, MLOps, Kubernetes, GCP, BigQuery, Airflow, Python, SQL,
Machine Learning, Recommender Systems, Terraform

Data Engineer

Flowbox AB

Internet & IT

50-250 team member


Flowbox is a SaaS startup offering a User-Generated Content platform for e-
commerce brands.

  • Snowflake Data Platform: Designed a cloud-native data platform from scratch on Snowflake and AWS (Glue, Athena, MWAA) to power customer-facing analytics, handling millions of daily tracking events.
  • Stream Processing & ELT: Built batch and streaming data pipelines to ingest high-volume event data into the warehouse and transform it using both DBT and Spark.
  • DevOps & IaC: Introduced AWS CDK for infrastructure-as-code and CI/CD pipelines, significantly simplifying deployments.

Skills: Data Engineering, Data Modeling, Snowflake, AWS (Glue, Athena, Kinesis,
Lambda, S3), Spark, Airflow, DBT, Python, SQL, DevOps, IaC (Terraform, CDK)

Senior ML Engineer / Data Scientist

Klarna Bank AB

Banking & Financial Services

1000-5000 team member

  • Spearheaded the development of a new model training and deployment framework in AWS and Sagemaker, providing semi-automatic training and deployment pipelines and drastically reducing time-to-market for new models
  • Created a template for building PD-models, that promotes standardization and best practices across projects and is now used by several teams
  • Developed multiple probability-of-default models, from the first data analysis to the final production deployment, including a new model for UK paylater that cut losses in half
  • Experimented with a wide range of technologies and ML techniques, including Deep Learning, Bayesian ML, Bayesian optimization, and model explainability (e.g. SHAP) to improve our models

Skills: Data Science | Machine Learning | MLOps | AWS (e.g. SageMaker, StepFunctions, Lambdas, Redshift, CDK) | Python | SQL | Hadoop | Spark | Airflow | IaC (CDK) | CI/CD

ML Engineer / Data Scientist

Klarna Bank AB

Banking & Financial Services

1000-5000 team member

  • Spearheaded the development of a new model training and deployment framework in AWS and Sagemaker, providing semi-automatic training and deployment pipelines and drastically reducing time-to-market for new models
  • Created a template for building PD-models, that promotes standardization and best practices across projects and is now used by several teams
  • Developed multiple probability-of-default models, from the first data analysis to the final production deployment, including a new model for UK paylater that cut losses in half
  • Experimented with a wide range of technologies and ML techniques, including Deep Learning, Bayesian ML, Bayesian optimization, and model explainability (e.g. SHAP) to improve our models

Skills: Data Science | Machine Learning | MLOps | AWS (e.g. SageMaker, StepFunctions, Lambdas, Redshift, CDK) | Python | SQL | Hadoop | Spark | Airflow | IaC (CDK) | CI/CD

Full-stack Developer

Causality Agency AB

Internet & IT

10-50 team member

  • Developed and deployed several apps and backend applications using ReactNative, node.js, and AWS
  • Client assignment with Itch: Extended and maintained the back-end of the Hyresgästföreningen negotiation portal as well as training the new in-house developers

Developer - C/C++ (part-time)

Marco GmbH

Industry & Mechanical Engineering

250-500 team member

Developed a simulation environment to automate software tests of mining controllers, which included the simulation of the physics of coal mines, the mining robots, and their sensors

Developer - C/C++

Marco GmbH

Industry & Mechanical Engineering

250-500 team member

Developed a simulation environment to automate software tests of mining controllers, which included the simulation of the physics of coal mines, the mining robots, and their sensors

Certificates

Professional Data Engineer - Google Cloud Certified

Google

2022

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