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Senior Data Solutions Engineer designs and leads cloud data platforms (Azure/AWS) and data pipelines, mentors teams, and translates business needs into scalable, secure architectures to deliver client value.
Build a centralized data platform using Python, PySpark, and AWS services to store and process event data, enabling large-scale marketing campaigns.
Staff Data Engineer modernizes enterprise-scale data pipelines using PySpark, AWS Glue, and Airflow, while setting engineering standards and coaching teams on cloud-native architectures.
Lead modernization of large-scale data pipelines using PySpark, Python, AWS Glue, Spark, and Airflow in a regulated environment.
Staff Data Engineer modernizing large-scale cloud data pipelines using PySpark, AWS Glue, and AI-assisted tools to set engineering standards and drive scalable data solutions.
Lead a team to design and build geospatial data pipelines and cloud infrastructure on AWS, using QGIS, FME, and PySpark to power a major UK government digital transformation project.
Design and harden enterprise-scale Databricks data platforms for clients, building guardrails and automation so teams can safely build on the platform using PySpark, Structured Streaming, and AWS-native patterns.
Design and build cloud-based data pipelines and ETL/ELT processes using Python, PySpark, AWS/Azure services to support insurance analytics and modern data architecture.
Build and maintain automated test frameworks for AWS data services using Python, pytest, and boto3 to validate functionality and performance of cloud platforms like S3, Redshift, and Glue.
Build and maintain automated test frameworks for AWS data services using Python, pytest, and boto3 to validate functionality and performance of cloud platforms.
Designs and builds cloud-native data pipelines on AWS using Glue, EMR, and Athena with PySpark and SQL to transform large datasets for enterprise clients.
Designs and builds cloud data platforms on AWS, Azure, and GCP using SQL, Python, and ETL best practices for enterprise clients.
Design and maintain scalable data pipelines on AWS using Glue, EMR, and Athena, with PySpark and SQL for transformations and DevOps practices via Terraform and GitLab.
Build and maintain AWS-based data pipelines and analytics platforms using services like Glue, Redshift, and SageMaker to enable data-driven insights and reporting.
Builds and optimizes data pipelines and warehouses using AWS services, Teradata, and PySpark for a telecom-focused enterprise platform.
Lead a team to build and optimize large-scale data pipelines and warehouses using PySpark, AWS Glue, EMR, and Redshift, ensuring performance, quality, and security.
Design and deploy AI/ML pipelines and GenAI apps to personalize trading experiences, predict customer churn, and automate marketing workflows using Python, SQL, and AWS SageMaker.
Lead the design and operation of Klarna’s AWS-based analytical data platforms, building scalable pipelines and warehouses with Spark, Iceberg, Redshift, and Terraform.
Build and scale the data infrastructure that powers LLM training, fine-tuning, evaluation, and RAG systems using cloud tools like AWS Glue, EMR, and Kubernetes.
Lead big-data engineering projects for financial-services clients, designing Hadoop-based pipelines, cleaning messy data, and delivering actionable insights using Java/Python and ETL tools.
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