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AESYS is seeking a Data Engineer to design and implement data pipelines on Azure using Databricks, PySpark, and ADF. The role involves working with Delta Lake architectures and managing data integration from various sources in a hybrid or remote environment.
Data Architect designing and operationalizing cloud-native data processing systems and large-scale ELT pipelines on GCP, focused on security, scalability, and compliant data management.
Design and optimize data pipelines and platforms for next-generation telecom networks, collaborating with OSS architects and international stakeholders using ETL/ELT, GCP (Dataflow, BigQuery), Databricks, Kafka, and REST/GraphQL APIs.
Data Engineer designing scalable data pipelines, workflow automation with AI Agents, and maintaining a cloud-based Data Platform on GCP for a large omnichannel home-improvement retailer.
As a Customer Engineer specializing in Data Analytics, you will partner with sales teams to design data foundation architectures, develop MVPs, and drive technical adoption of Google Cloud. The role blends technical sales, hands-on prototyping, and consulting to solve customer analytics challenges.
Data Engineer building modern data platforms, pipelines, ETL/ELT processes, data modeling, and warehouses in AWS/Azure/GCP cloud environments within a consulting firm, collaborating closely with developers and customers.
Data Engineer at an IT consultancy building modern data platforms, ETL/ELT pipelines, and data warehouses on cloud (AWS/Azure/GCP) using SQL and Python for various client projects.
Own and maintain ETL/ELT data pipelines, databases, and workflow orchestration for a credit risk research initiative at NUS's Asian Institute of Digital Finance, with opportunities to contribute to AI/LLM research.
Design and implement Azure data pipelines using Databricks, PySpark, and ADF, collaborating with data platform teams on Delta Lake architectures with focus on security, governance, and performance.
Data Engineer designing and managing data pipelines on Azure, working with ETL/ELT, Azure Databricks, and PySpark in an international, hybrid/remote context.
Design, build, and operate large-scale batch and real-time data pipelines on Google Cloud Platform, working with BigQuery, Dataflow, and other GCP managed services to turn raw data into business insights.
Data Engineer building a central Databricks-based data platform focused on AI applications, developing data pipelines, modeling data structures, and building data products using Python, SQL, and ETL/ELT.
Designs and optimizes data pipelines and data platforms for next-generation telecom networks, collaborating with OSS architects and international stakeholders using ETL/ELT, GCP (Dataflow, BigQuery), Databricks, Kafka, and REST/GraphQL APIs.
Design, build, and operate large-scale GCP data processing pipelines using ELT principles, turning raw data into actionable business insights with a focus on security and scalability.
Azure Data Engineer bridging Data Science and Data Engineering, building data acquisition, transformation, and loading pipelines into data lakes for analytics and ML using Azure Data Factory, Synapse, Databricks, and Spark.
Data Engineer building scalable data pipelines, ETL/ELT processes, and integrating heterogeneous data sources in an enterprise environment using Python/Scala, SQL, Spark, and cloud platforms (AWS/Azure/GCP).
Data & Analytics Engineer designing BI solutions, ETL processes, and data models using Power BI, SQL, and the Microsoft/Azure data ecosystem.
Senior Data Engineer designing and deploying ELT pipelines on Snowflake using dbt, Python, and Terraform for a financial services firm's data platform.
Backend Engineer (Python) building scalable services, APIs, and LLM-powered features for an AI-first finance platform, working with Python, AWS, SQL, and REST APIs.
Build and optimize financial reporting pipelines and data warehouses using PostgreSQL and Apache Airflow, collaborating with stakeholders to deliver accurate, automated analytics.
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