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Senior Data Engineer at Data Reply (Reply Group) in Paris, building AWS data pipelines and use cases for clients: mapping cloud data sources/flows, industrializing data processing, creating dashboards and reporting tools, and writing unit/integration tests. Needs 5-8 years of data engineering experience with an AWS solution in production.
Senior Data Engineer at Data Reply (a Reply group subsidiary specializing in AI-powered data and analytics services) in Paris. The role involves designing and industrializing data pipelines on AWS, mapping data flows, and building robust processing using ETL tools (Glue, DBT, Airbyte) and real-time technologies (Kafka, Kinesis, Databricks).
Build and operate data and analytics services that power critical markets risk decisions at scale. In this senior, hands-on role, you will lead complex engineering initiatives across a modern cloud and big data stack…
Senior Data Engineer owning NimbleRx's end-to-end data platform in Toronto: building batch/streaming pipelines with PySpark/EMR, Kinesis, Lambda and Iceberg on S3, modeling the warehouse, tuning Postgres-backed services, and owning security/compliance so product, analytics, and data science teams can move faster.
Flybuys is hiring a Lead Data Platform Engineer to own its end-to-end data platform: designing scalable data models and pipelines, leading distributed teams across time zones, and establishing governance, security, and operational standards to deliver trusted, governed data products for members and partners.
Hands-on Data Engineer with product ownership: you architect and run ProfitPeak's customer-facing Databricks lakehouse and ClickHouse serving layer, building multi-tenant attribution, revenue and marketing analytics data pipelines and MLOps models that retail brands and their AI agents act on.
Lead data platform and pipeline engineering end-to-end at Flybuys, Australia's largest loyalty rewards program, combining hands-on data engineering with people leadership. Core stack: SQL, Python, Airflow, dbt, Fivetran, Hightouch, BigQuery/Snowflake, AWS/Azure and streaming technologies.
Data Engineer at Boehringer Ingelheim's IT Enterprise Data, AI & Platforms team, designing and maintaining ETL pipelines and cloud data infrastructure for Finance, Procurement, HR, Sustainability and IT domains. Core stack includes AWS data services (S3, Kinesis, Glue, Lambda), Snowflake, dbt, SnapLogic and the Apache ecosystem (Spark, Kafka, Airflow).
We are looking for a Data Engineer to design, build, and support reliable data ingestion and transformation pipelines on AWS and Databricks. The role will work with architects, engineers, QA, and business teams to…
A data engineer in Dublin who builds and enhances pipelines into HMH's Enterprise Data Lake and Warehouse using PySpark on AWS Glue, Kafka Connect, and Kinesis Firehose. Day to day involves curating datasets with data science, learning science, and product teams, building dashboards, and automating processes with infrastructure-as-code.
Data engineer on HMH's data engineering team in Dublin, building and maintaining pipelines that feed the Enterprise Data Lake and Data Warehouse using PySpark on AWS Glue, Kafka Connect, Kinesis Firehose, and Terraform-managed AWS infrastructure. Works closely with data science, learning science, and product teams to curate datasets and power analytics and BI.
Senior Software Engineer on HMH's Dublin data engineering team, building data pipelines into the Enterprise Data Lake and Warehouse on AWS. Day to day: data modelling, pipeline development with PySpark, Kafka Connect and Kinesis, infrastructure automation with Terraform, SQL work, and mentoring junior engineers.
A senior hands-on data engineer / platform lead who designs, builds, and owns end-to-end data pipelines and a modern data platform (lakehouse/warehouse), ensuring data quality, governance, and observability while mentoring junior engineers. Core stack: SQL, MS Fabric, Data Factory, Power BI, and AWS/Azure.
Senior backend engineer at Dis-Chem Life (the insurance arm of pharmacy group Dis-Chem) who designs, builds, and operates secure, scalable cloud-native backend services and APIs on AWS. Day-to-day work spans domain-driven architecture, data stores, event-driven messaging, observability, and security for a regulated insurance platform.
Senior DevOps/Cloud engineer contracting through Zortech Solutions to design, build, and support AWS cloud environments for a contact center solution, leading an Amazon Connect implementation (call/queue flows, agent experience, recording, metrics, Contact Lens). Heavy AWS stack with CloudFormation IaC, CI/CD (GitLab), Docker/Kubernetes, and monitoring; hybrid Toronto role, 3 days onsite.
Contract backend developer (6-12+ months) building and maintaining Ruby on Rails and Java systems with a focus on performance, scalability, and security. Day-to-day includes AWS operations, database work across MySQL/PostgreSQL/MongoDB, Docker/Kubernetes orchestration, CI/CD, testing, documentation, and on-call production support.
Capgemini is hiring an AWS Data Engineer for an onsite-hybrid role in New Jersey to design scalable AWS data architectures, build ETL/ELT and streaming pipelines, and manage data lakes and warehouses using S3, Redshift, Snowflake, Glue, EMR, Spark, Python/Scala, plus CI/CD and infrastructure-as-code tooling.
Capgemini is hiring an Architect in Gdańsk for its Insights & Data practice to design cloud big-data solutions (data lakes, streaming, modern DWH) on AWS, Azure or GCP, code in Python/Scala/Java, and technically lead delivery teams. Hybrid work split between a modern office and home.
Capgemini is hiring an AWS Data Engineer in New York, NY to design, build, and optimize scalable ETL/ELT data pipelines, data lakes, and warehouses on AWS (S3, Glue, Redshift, Lambda, Kinesis), supporting analytics, reporting, and data-driven decisions while collaborating with data scientists, analysts, and DevOps teams.
A code-first data engineer at Capgemini's Data Platforms team building scalable data pipelines, streaming and orchestrated workflows, and containerised services for UK Defence customers, including running ML/GenAI workloads in secure, sometimes air-gapped environments. Core stack: Python, Kafka/Spark, Airflow, Docker/Kubernetes, CI/CD, AWS/Azure/GCP.
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