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Experteer Overview Todos los posibles candidatos deben leer con atención los siguientes detalles de este trabajo antes de presentar una candidatura. In this role you design, build and optimize scalable data solutions…
Senior Data Engineer on an Intellias delivery team migrating a global asset manager's enterprise data platform to Azure Databricks, building medallion lakehouse pipelines (Delta Lake, Unity Catalog, Lakeflow, Structured Streaming) in production, owning architecture on a workstream, and mentoring a mid-level engineer. Remote from Spain with a Spanish employment contract.
Senior Data Engineer joining the Data team in Barcelona to build and maintain the data infrastructure behind Titan OS's smart-TV platform — designing data pipelines and AWS ingestion/processing infrastructure, adding data observability, and standardizing DataOps practices. Core stack includes Python, SQL, Airflow, and AWS services.
A hands-on senior data engineer designs and builds secure, scalable Snowflake pipelines, data models, and analytics for a regulated banking environment, working daily with BigQuery, Airflow, and GCP. The role covers end-to-end development plus CI/CD, security, governance, performance, and cost optimization.
A senior Java developer/architect extends a banking client's internal test data platform (an ETL tool that extracts, transforms, masks and loads test data) by adding MongoDB and PostgreSQL support alongside existing Oracle, SQL Server, DB2 and SAS connectors. Day to day: analyzing the architecture, building the new database integrations, writing docs and handing over knowledge, with a hybrid setup
Senior BI Consultant building and maintaining BI and data warehousing solutions: designing ETL/ELT pipelines into AWS Redshift, automating workflows with Python, and applying data science/analytics. Core stack includes Python, AWS (Lambda, S3, Redshift), SQL, and Power BI, with a focus on data governance and mentoring.
Senior data integration engineer (10+ years) who designs, builds, and operates production-grade pipelines connecting a cloud data platform to an existing data-processing application, using Python, SQL, REST APIs, and XML/JSON, with strong batch and change-data processing, error handling, and record traceability.
Senior Data Engineer who designs, builds, and owns scalable data platforms on Azure for retail, wholesale, and distribution clients — developing enterprise data warehouses, ETL/ELT pipelines (ADF, Databricks, Airflow), PySpark/Delta Lake transformations, and Power BI models.
Synthlane Technologies is hiring Mid and Senior Data Engineers to build a privacy-preserving data platform. Day to day you design and run production-grade AWS data pipelines (Python, SQL, Spark, Parquet) that de-identify and curate operational data into secure, AI-ready datasets, using orchestrators like Airflow, Dagster, or AWS Step Functions with strong data-quality and SRE-style practices.
Synthlane Technologies is hiring a Senior Data Engineer in Hyderabad to design, build, and maintain scalable data pipelines and distributed data-processing applications using Java, Apache Spark, and AWS (S3, EMR, Glue, Redshift, Lambda). Day-to-day work covers ETL/ELT development, Spark performance tuning, data modeling, and production support.
A hands-on Senior Snowflake Data Engineer at Paar Systems in Sydney who owns end-to-end data pipelines and data products in a regulated banking environment. The role centers on designing secure, scalable Snowflake architectures, building CI/CD pipelines, enforcing governance, and optimizing performance and cost across cloud platforms.
Senior Data Engineer at Moniepoint builds and maintains large-scale data pipelines and optimizes the data platform for speed, scalability, and cost, supporting teams across a payments and banking platform. Core stack: SQL, Python, cloud platforms (Google Cloud/AWS/Azure), and Git.
Senior Data Engineer at PUR, a climate-focused B Corp, building and maintaining scalable Python ETL/ELT pipelines, data models, and data quality controls that power analytics and reporting. The stack centers on workflow orchestration (Airflow, Prefect, or Dagster), a cloud data platform (preferably Azure), Terraform, and Git-based engineering practices.
Build and own parts of F-Secure's Enterprise Data Platform in Helsinki: ingest data from business systems, model it in Data Vault 2.0, and build Power BI semantic models and secure APIs feeding reporting, analytics, and AI agents. Core stack: SQL, Agile Data Engine, Databricks/AWS (migrating from Snowflake/Azure), REST/OAuth, with daily use of AI coding agents like Claude Code.
Senior Data Engineer building an AI-powered, governed analytics 'Intelligence Layer' on Databricks for what appears to be a travel/aviation client. Day to day: designing data pipelines and curated datasets in Unity Catalog, defining Metric Views, tuning Genie Agents, and building multi-agent AI orchestration with MLflow tracing, using Python and SQL.
Senior Data Engineer on a high-load network-traffic post-analysis system at a Russian telecom-infrastructure vendor (Rostelecom group). Day to day: designing batch/streaming pipelines, leading the Hadoop → S3/Iceberg migration, optimizing Spark and Trino for near-real-time processing. Core stack: Spark, Kafka, Python, Iceberg, Trino.
Lab49/ION is hiring a Mexico City-based Senior Data Engineer to design, build, and operate scalable data platforms for market and credit counterparty risk in financial services. Day-to-day work centers on Python, AWS, Airflow, and Snowflake, plus CI/CD automation, monitoring, and stakeholder collaboration in an agile team.
Build and maintain Rightmove’s GCP-based data platform, owning scalable pipelines, infrastructure as code, and internal tooling to power property data for millions of UK users.
Build and lead Rightmove’s scalable data platform, designing pipelines and tools for analytics, ML, and AI initiatives that power the UK’s largest property marketplace.
Senior Data Engineer in Moscow building and optimizing scalable batch and streaming data pipelines using Airflow, Spark, Hadoop and ClickHouse, ensuring data quality and delivering features for analytics and ML, including work on AI/ML services in the corporate AI center.
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