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Lead Data Engineer at eDreams (online travel agency) in Barcelona, driving the data engineering strategy and delivering scalable data products for AI-driven Performance Marketing. Core stack includes Python, advanced SQL, dbt, and Dagster (Airflow a plus), with ETL/ELT, data modeling, and governance; hybrid work model.
Cloudbeds is hiring a hands-on Tech Lead Data Engineer & Data Architect to shape its Snowflake/dbt-based analytics platform — owning data modeling, pipelines, DataOps/CI-CD, governance, cost tuning, and AI-readiness for a fully remote senior Data Analytics & BI team.
Data engineer focused on NLP: deploys and maintains the local node of the national federated model-evaluation platform (PARTAGES), prepares and documents local medical datasets, runs model evaluation campaigns, and builds Dagster-orchestrated ETL pipelines for medical report text analysis, including pseudonymization and automated medical coding use cases.
Thoughtworks seeks a Tech Principal / Forward-Deployed Engineer in Riyadh to lead pods that turn client ideas into production AI-first products on a 3-day/3-week/3-month cadence. The role owns architecture, stack selection, and LLM engineering (Python/TypeScript, cloud, RAG, agent frameworks) while advising executives on Vision 2030-era digital programs.
Build and maintain scalable data pipelines and automated reporting for shop performance analysis and retail media partners at a fashion e-commerce company. Core stack includes SQL with BigQuery, dbt, orchestration tools (Dagster/Airflow), and web analytics (GA4), plus revenue attribution modeling.
Analytics Engineer at ABOUT YOU (a fashion e-commerce company) in Berlin, designing and maintaining scalable data pipelines, automated reporting, and revenue attribution models for shop performance and retail media. Core stack: SQL, dbt, BigQuery/Redshift, and orchestration tools like Dagster or Airflow.
Build and maintain scalable data pipelines, warehouses, and analytics tooling for a virtual behavioral healthcare provider, using Python, SQL, Snowflake, and Dagster/Airflow.
Designs and maintains data pipelines, warehouses, and analytics tooling for a virtual behavioral healthcare provider, using Python, SQL, Snowflake, and Kafka.
Senior data engineer joining a small, senior Data & Analytics team supporting a real estate investment firm's Snowflake platform fed by 40+ sources. Day to day: stabilize inherited pipelines, enforce data modeling standards, make reporting reliable, and automate manual work. Core stack: Snowflake, advanced SQL, dbt, Airflow/Dagster.
Early-career Data Engineer on Atlas Air's Data Platform and Engineering team, building and operating batch and streaming data pipelines, transformations, and data models on Databricks/Spark to support analytics, data science, and AI/ML at a global cargo airline.
Senior data engineer joining a small Data & Analytics team serving a real estate investment firm's client: inheriting and stabilizing an existing Snowflake platform with 40+ data sources, fixing unreliable pipelines, and automating manual reporting. Core stack is Snowflake, advanced SQL, dbt, and Airflow/Dagster.
Senior Data Platform Engineer on Scopely's Playgami team in Barcelona, building and operating the shared GCP/BigQuery data platform behind 15+ games and 60TB of daily data. Day-to-day work spans Terraform-based infrastructure, CI/CD, IAM and least-privilege access, Airflow/Cloud Composer reliability, monitoring, and cost optimization using Python and SQL.
Builds and ships Sber Bank's recommendation models to production: develops end-to-end ML and data-processing pipelines over petabyte-scale data with PySpark, writes efficient PyTorch training/inference code on GPU clusters, and optimizes high-load recommendation services. Stack: Python, PySpark, Airflow, Kubernetes, PyTorch, MLflow.
Platform Engineer on the data & AI platform teams at Sweden's central bank, maintaining and developing Riksbanken's in-house data/AI platform (Kubernetes, S3 object storage, Python, mainly on-prem with some Azure) — automating CI/CD and drift, running containerized services, and driving platform adoption with business users.
Staff Data Engineer at Meeru AI Inc in Canada to own data platform subsystems end to end — building production-grade pipelines, connectors, and warehouse transformations that feed analytics and AI layers. Core stack: dbt, orchestration with Airflow or Dagster, and Python tooling, with close collaboration on data contracts.
Data Engineer III building end-to-end ETL pipelines, dbt semantic models, and infrastructure for ZoomInfo's Strategic Partnerships data platform. Day to day: scoping data needs with business stakeholders and shipping production pipelines using Snowflake, BigQuery, Airflow, Fivetran, dbt, Databricks, and Terraform on AWS/GCP.
Data Engineer at Heylist, a creator-marketing platform, owning the data platform end to end: building ingestion pipelines from APIs like Meta and TikTok, modeling the warehouse, and shipping data services that power product features and analytics. Core stack is Python, SQL, Postgres, and Azure, with dbt, Snowflake, Airflow, and Terraform as nice-to-haves.
Sofina, an investment holding company, is hiring a Data Engineer in Singapore to own and evolve its data platform and build AI/LLM-powered internal tools for investment research. The role is hands-on across data engineering and back-end work — building pipelines with Python, SQL, dbt, Dagster and Snowflake/Fabric, exposing enterprise knowledge to LLMs, and mentoring junior engineers.
Six-month renewable contract in Geneva (hybrid) to design, build, and operate an enterprise GCP data platform: ELT pipelines on BigQuery and Cloud Composer/Airflow, analytics models in dbt, GitLab CI/CD, Terraform infrastructure-as-code, and Python automation, plus production support and collaboration with analytics and business teams.
Senior ML Data Engineer at GoWish (Ønskeskyen), a wish-list and social shopping platform. You'll own offline-to-online feature infrastructure — syncing warehouse data (BigQuery) into low-latency stores (AlloyDB, Redis, Feature Stores) via Airflow, dbt, Terraform and Docker to power real-time recommendation and search, in a hybrid setup from the Copenhagen office.
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