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Senior Data Engineer at hiberus in Madrid, designing data models and transformation pipelines with DBT on Snowflake, building Master Data Management logic in the Data Warehouse, and orchestrating data workflows with Apache Airflow. Core stack: Snowflake, DBT, Airflow, Python.
Data Engineer at Kyndryl's Applications, Data & AI practice building modern cloud-native data platforms on Google Cloud Platform. Day to day: designing and maintaining ETL/ELT pipelines (BigQuery, Dataflow, Pub/Sub, Composer, Dataproc), developing data models for analytics and AI, and implementing data quality and governance controls.
Senior Data Engineer at BCNC Group building unique, reliable, reusable master data: designing Airflow DAGs to integrate sources and APIs, writing SQL/dbt transformations and data quality processes on Snowflake, and partnering with Data Engineering, BI, development, and business teams on quality controls, traceability, and golden records.
Middle-level Data Engineer in Madrid (hybrid, 2 days on-site, long-duration engagement) for an industrial-sector client. Day to day: designing Snowflake schemas and tables, building dbt models with tests and lineage, writing advanced SQL, and working in Agile with Git and CI/CD pipelines.
Data Engineer working fully remote from Spain on international logistics and e-commerce data projects: designing scalable ETL/ELT flows, leading the Apache Airflow to GCP Dataform/BigQuery migration, building real-time event messaging with Pub/Sub, optimizing the BigQuery data warehouse, and supporting MLOps operations.
Senior Data Engineer in Spain designing and evolving a data platform: building robust, scalable data pipelines and analytical models. Day to day involves orchestrating with Airflow, modeling with dbt, working with Snowflake and cloud data environments, and SQL/Python transformations with testing, monitoring and cost optimization.
Senior Data Engineer who designs and builds data pipelines, data models, and scalable, maintainable solutions on a cloud data platform, working daily with Airflow, dbt, and Snowflake while collaborating with Data Engineering, BI, and business teams, with strong focus on data governance and quality.
Senior Data Engineer at Plain Concepts (Spain) building tailor-made data solutions for clients: developing ETLs with Spark (Python/Scala), scalable cloud pipelines on Azure/AWS, and transformations with Snowflake and DBT, working in agile, multidisciplinary teams with optional fully remote work.
Remote (EU) data engineering role at an Enterprise AI company based in Paris: build the ingestion, transformation, and data-processing infrastructure behind production AI, enterprise search, and RAG applications. The focus is on reliable production data pipelines, vector databases, and search infrastructure rather than LLM specialization.
BCNC Group is hiring a Senior Data Engineer (remote, Spain) to join a data team in transformation, building reliable and reusable master data. Day to day: designing Airflow DAGs, SQL and dbt transformations, working with Snowflake, and running MDM processes like matching, deduplication and golden record generation.
Founding-level data engineer at a Sequoia-backed startup building AI-powered investigation software and hardware for UK police forces. You'll own the data layer, building ETL/ELT pipelines to ingest and reconcile messy legacy police data using AWS, Terraform/Pulumi, Python and SQL, working from Central London 2-3 days/week.
Hands-on engineering manager leading a data engineering team at Hargreaves Lansdown (UK investment platform), owning end-to-end delivery of data pipelines, platform operations, engineering standards, and cost/performance in a regulated financial services environment. Core tech includes cloud data platforms (Snowflake/BigQuery/Redshift) and orchestration tools (Airflow/Dagster).
A hands-on Senior Data Engineer in Manchester designs and builds scalable ETL/ELT pipelines, Python data services and a cloud-native AWS data platform (Glue, Step Functions, Athena, S3, dbt), working with large datasets while shaping data quality, governance and engineering standards and mentoring colleagues.
Principal Data Engineer at Funding Circle, a London-based small-business lending fintech (hybrid, 2 office days/week). You own the data platform strategy, lead the migration to a future-state Snowflake/AWS platform, and set architecture, governance, and data-product standards across the data estate.
Builds and optimises data pipelines and reliable data models on AWS and Snowflake (using dbt, SQL, Python) for a PE-backed business in Hemel Hempstead, hybrid 3 days onsite. Projects span predictive forecasting, dynamic pricing, workforce optimisation and customer analytics, with genuine ownership of technical decisions.
Senior Data Engineer at Maeve AI in London, owning the data side of an AI product for fashion brands: modelling and cleaning messy retailer data in dbt and Snowflake, building ingestion from Shopify, PLMs and customer warehouses, and serving a Cube.dev semantic layer that powers dashboards and LLM agents.
Remote contract Data Engineer who designs, builds, and optimizes ELT/ETL pipelines and cloud data warehouse architectures on Snowflake, Databricks, or BigQuery using Python, SQL, dbt/Spark, and orchestrators like Airflow. Also handles data quality gates, query/cost tuning, and data access governance.
Consulting role at Attain Partners serving higher education clients: acts as both Snowflake solution architect and hands-on developer — leading discovery and design workshops, building data models and ETL/ELT pipelines, and optimizing/troubleshooting Snowflake environments. Core tech: Snowflake, advanced SQL, cloud data platforms.
Lead Lemonade's Analytics Enablement team, building and maintaining the enterprise data foundation — data models, semantic layers, dashboards, and BI tools — that powers Marketing, Product, and Insurance analytics. Core stack includes Snowflake, Looker, GitHub, and dbt, with an AI-first approach.
A hands-on engineering manager who leads a small data platform team and personally owns Snowflake architecture, security, governance, performance, and cost, with operational oversight of AWS RDS PostgreSQL. Day-to-day involves automation with Terraform, Python, and dbt, CI/CD practices, on-call escalation, and enabling analytics/ML/AI workloads.
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