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The Data Engineer will design and implement data pipelines to transform raw robot and external datasets into structured, reproducible formats for training AI models. The role focuses on building validation suites, managing dataset versions, and creating tools to support ML teams in the robotics center.
Company Description NCS is a leading technology services firm that operates across the Asia Pacific region in over 20 cities, providing consulting, digital services, technology solutions, and more. We believe in…
Role Summary You are an autonomous AI Engineer, responsible for creating the harness for designing and building the AI harness, agent framework, and reusable engineering components required to operate a modern data…
Are you an experienced Big Data professional eager to tackle complex challenges in a dynamic banking environment? EPAM is seeking a dedicated Senior Big Data System Engineer (Platform Engineer) to maintain, optimize…
Top 3 Reasons To Join Us Salary and bonus based on ability Young and fun working environment Opportunities to study and work abroad. The Job Design and build cloud-based data pipelines with scalability and reliability…
Nagyméretű adatkészletek feldolgozását és elemzését támogató megoldások fejlesztése, Adatintegrációs, ETL/ELT- és adattranszformációs folyamatok kialakítása és optimalizálása, Data Lakehouse architektúrához kapcsolódó…
Join the Team Modernizing Medicine At ModMed , we’re not just building software—we’re reimagining the healthcare experience. Founded in 2010 by a practicing physician and a successful tech entrepreneur, we took a…
Role: Azure Data Engineer with Fabric Location: Deerfield Beach, FL Duration: 6-12 Month Contract to Hire NEED AN SME WITH FABRIC. Senior Data Engineer – Azure & Microsoft Fabric · The Senior Data Engineer designs,…
Data Platform Engineer at Macquarie Group's Data Services team in London, designing, building, and optimising a petabyte-scale cloud data lake and platform serving trading teams. Core stack is AWS (S3, EKS, Glue, Airflow, Trino, Redshift, Parquet, upcoming Iceberg) plus Python, SQL, and DevOps/CI-CD automation.
Data Platform Engineer at +Simple, a B2B insurtech in Marseille: keeps the group's data chain reliable (Airflow scheduling, monitoring, alerting, data integrations via S3, SFTP, SharePoint and APIs) and builds internal Python/FastAPI apps end to end, with Docker, GitLab CI/CD and Metabase; Spark/Databricks is a plus.
Data Engineer at SmartOSC in Hanoi building and maintaining enterprise ETL/ELT pipelines, data quality and master data management on Azure (Data Factory) and Snowflake, using SQL and Python. Requires 3-5+ years in data engineering and Japanese speaking skill (JLPT N2+).
Builds and operates the data platform that turns Smart TV viewing, ad, telemetry and partner data into governed data products for Advertising, Content, Sales and Finance teams. Daily work spans AWS/Snowflake pipelines, an Iceberg lakehouse on S3, Airflow (MWAA) orchestration, SQLMesh modelling, Terraform IaC and a shared Python SDK/CLI.
Data engineer at a Spanish tech consultancy building ETL/ELT pipelines for cybersecurity data: ingesting and correlating events from SIEMs, network sensors and OS platforms, and preparing datasets for AI (RAG, embeddings, semantic search). Core stack: Python, SQL, Kafka/Flink, PostgreSQL/Elasticsearch/ClickHouse, Docker/Kubernetes.
Senior Data Engineer in Dubai who leads the design, build, and optimization of batch and real-time data pipelines, owning data modeling, ingestion, and lakehouse platform reliability while mentoring the team. Core stack: dbt, Airflow, Spark/PySpark, Dremio/Iceberg on S3, Python, advanced SQL, and hands-on NoSQL stores.
Senior Data Engineer owning the design, build, and reliability of WatchGuard's cloud-native Azure data lakehouse — building ETL/ELT pipelines with Azure Data Factory and Airflow, modeling in Snowflake and dbt, and embedding data quality and observability with Elementary across Bronze/Silver/Gold Medallion layers.
Build and maintain real-time and batch data pipelines powering payments/financial analytics at DigiOutsource, part of NYSE-listed gaming group Super Group, based in Cape Town. Day-to-day: SQL optimization, ETL/ELT workflows, streaming with Kafka or RabbitMQ, and Python or Java, while helping shift toward cloud-native data platforms.
Senior Backend/Data Engineer designing and maintaining Python-based data pipelines and backend services. The role involves building ETL processes, integrating external systems, and managing cloud infrastructure on AWS and Kubernetes, with a focus on data-intensive systems and AI-assisted development.
Senior individual contributor who owns the reliability, performance, and scalability of Scribe's data tier: tuning PostgreSQL on Aurora Serverless V2, keeping Django ORM migrations safe at scale, running the Aurora→DMS→S3 Parquet→Snowflake CDC pipeline, and supporting OpenSearch, Redis, and message queues.
Director-level full-stack engineer on Morgan Stanley's FORT (Risk Technology) team in Bengaluru, building and maintaining the revenue-generating FS analytics platform. Day-to-day work spans multi-tier web apps: Java microservices, REST APIs, Angular front-ends, and heavy relational database work (DB2/Greenplum).
Data engineer on Jacobs' UK Data & Digital team, designing, building and maintaining modern cloud data platforms and ETL/ELT pipelines using AWS or Azure, preparing data in formats like parquet, avro and JSON to serve government, defence and regulated environments.