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This senior data engineer role involves designing, building, and maintaining scalable end-to-end data pipelines and architectures using Snowflake, dbt, and AWS. The position requires a candidate to own the full data lifecycle and support analytics within a Canadian financial services environment.
Senior Data Engineer (hybrid, 3 days in downtown Toronto) building and optimizing scalable ETL/ELT pipelines using AWS, Snowflake, Python, SQL, and Airflow for a wealth technology group in the financial sector.
The Senior Data Engineer will design, build, and maintain enterprise data pipelines and data warehouse solutions using SQL Server and SSIS. This role focuses on transforming raw data into actionable insights while ensuring data quality, security, and performance across the organization.
The Data Engineer designs and maintains data pipelines and integrations to support GEI's AI solutions and digital initiatives. The role involves building ingestion pipelines, managing data stores for RAG, and ensuring data quality and governance using Azure technologies.
The Data Engineer II will build and scale data pipelines using Spark, Scala, and AWS to process massive datasets into actionable telecom insights. The role involves collaborating with cross-functional teams to develop production-ready data products and optimizing system performance.
Hours: 35 hrs Hybrid Working (3 days a week) Closing Date: Sun, 13 Sept 2026 We're looking for a talented Data Engineer to help shape the future of our data platform. If you’re passionate about cloud technologies,…
About Us Arpeely is a Data-Science startup, leveraging data analysis, ML, engineering, multi-disciplinary thinking to gain a market edge and exploit hidden opportunities in real-time advertising. Processing over 350k…
Data Engineer with 3+ years experience working on data migration and modernization projects, requiring strong Python and SQL skills, data pipeline/ETL/ELT experience, and some exposure to AI/LLMs/Agentic AI frameworks.
Junior Data Engineer building and maintaining ETL/ELT pipelines, working with SQL transformations, Python scripting, and cloud data platforms in a high-volume fintech environment.
Design and maintain scalable cloud data pipelines, build ETL/ELT processes, model data, and ensure data quality while collaborating with data science and software teams using Python, SQL, and AWS/Azure.
Design, build, and optimize data pipelines ingesting from 40+ payment networks and internal systems using Python, SQL, and Airflow for a financial data ecosystem.
The Senior Data Engineer will build and maintain robust ETL/ELT pipelines to process data from payment networks and internal systems using Python, SQL, and orchestration tools like Airflow. The role involves collaborating with stakeholders to ensure data accuracy, security, and performance optimization.
The Azure Data Engineer will design and implement data pipelines for data lakes to support analytics and machine learning models. The role involves collaborating with architects and analysts while leading mid-sized teams using Azure and Spark/Databricks technologies.
The Azure Data Engineer will support Big Data projects by designing data pipelines, performing ETL/ELT processes, and migrating workloads to the cloud. The role requires expertise in Azure services, Spark, and programming languages like Python and Java to prepare data for analytics and machine learning.
The Data Engineer will design and implement scalable batch and streaming data pipelines on Google Cloud Platform. The role involves developing data-driven solutions using services like BigQuery, Dataflow, and Airflow to support enterprise-level data ingestion and processing.
Junior Data Engineer designing and developing scalable ETL/ELT pipelines and managing relational and NoSQL databases for enterprise projects at an Italian consulting firm.
Design, build, and optimize scalable data platforms on GCP (BigQuery, Cloud Storage, Cloud Composer) and dbt, defining ELT pipeline architecture to deliver reliable data across the organization.
The Senior Data Engineer will design and maintain data pipelines and analytical models within the Microsoft Azure ecosystem. The role focuses on building scalable data solutions using Azure Databricks, Data Factory, and advanced SQL and Python programming.
Senior Data Engineer designing and maintaining scalable data pipelines on Azure (Databricks, Data Factory) using Python/Spark, collaborating with Data Science and Analytics teams.
Keepler is seeking a Data Engineer to implement data models, orchestration flows, and governance strategies using PySpark and Palantir Foundry. This is an on-site role focused on building data pipelines and ensuring data security and quality for clients.
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