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Build and maintain cloud-based data pipelines in Python and SQL, design modern data platforms (Data Lake, Warehouse), and ensure data quality and observability for analytics and AI projects.
Build and optimize scalable data pipelines and lakehouse infrastructure (Spark, Databricks, Snowflake) for a SaaS data-management platform, and help kick-start early AI use cases.
Build and maintain scalable data pipelines on GCP using Python, SQL, Spark, and Delta Lake, collaborating with engineers to support data infrastructure.
Lead Data Engineer designing and maintaining Databricks/Spark pipelines in Python and SQL to migrate and industrialize a new energy-sector data platform, ensuring performance, reliability, and cost control.
Build and maintain scalable data pipelines on Databricks, integrating diverse sources and industrializing ML models for enterprise clients.
Senior Data Engineer builds and scales Databricks/AWS pipelines to industrialize analytics and ML prototypes into robust, governed solutions for an energy-sector platform.
Build and optimize Azure Lakehouse data pipelines for AI projects using Databricks, ensuring high-quality datasets and performance.
Design and build scalable data pipelines and cloud-based data platforms for clients, using tools like Terraform, Spark, Kafka, and Snowflake.
Design and build scalable cloud data architectures (Snowflake, GCP/AWS/Azure) and robust ETL pipelines, then expose clean, governed data to analytics and AI teams using dbt and modern data-stack patterns.
Build and maintain scalable data pipelines and cloud infrastructure for a media company’s data platform using Python, Spark, SQL, GCP, Airflow, and Terraform.
Build and maintain scalable data pipelines and cloud infrastructure on GCP, using Python, SQL, Spark, and Terraform to support analytics and AI solutions.
Designs and operates AWS data pipelines in Python, builds Spark workloads, and transforms raw adserver/CRM data into KPIs for media teams.
Build resilient data pipelines and self-serve tooling for a crypto market maker, normalizing market, trading, and portfolio data in real time for desks, risk, finance, and research.
Build and maintain scalable data pipelines and warehouses for analytics, using cloud tools like AWS and Snowflake, orchestration platforms such as Airflow, and data modeling best practices.
Designs and maintains scalable cloud-based data pipelines and storage using Python, SQL, and cloud platforms like Azure/AWS/GCP to ensure reliable, high-quality data for business operations.
Build and optimize scalable data pipelines and lakehouse infrastructure (Spark, Databricks, Snowflake) for a SaaS data-management platform, with early AI use-case enablement.
Backend developer building secure .NET APIs and managing ERP data flows in SQL Server, with optional Azure cloud services.
Build and scale data pipelines for TV and advertising analytics using Spark, Scala, and AWS; own resilient, cloud-native platforms handling terabytes daily.
Senior DevOps/Platform Engineer designs, builds, and secures Kubernetes and Spark-based platforms with Linux, Docker, and Python/Bash in a security-cleared environment.
Builds scalable cloud-native apps in Java/Python and integrates AI tools to automate coding, testing, and DevOps workflows for enterprise solutions.
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