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Senior Data Engineer builds and maintains scalable data pipelines and warehouse models to deliver trusted insights for Salesforce’s AI CRM and Slack integrations.
Design, automate, and maintain cloud infrastructure for demos and POCs using Terraform, Ansible, and CI/CD pipelines to support Salesforce’s AI CRM sales cycles.
Build and operate cloud data pipelines and services using Python, Google Cloud, and Terraform to power PAYBACK’s data-driven marketing platform for 31 million users.
Analyze payment datasets to spot trends, build analytics pipelines, and deliver optimization recommendations for merchants using Python, SQL, and PySpark.
Build and scale data infrastructure for AI workloads, including ingestion pipelines, data lakes, and Kubernetes-based processing systems.
Build and scale Databricks-based data pipelines and ETL for Adobe’s Pro Design products, enabling AI-driven analytics and experimentation with telemetry and governance in Unity Catalog.
Build and optimize enterprise-scale data pipelines and warehouses on Snowflake using Python, PySpark, AWS, and Airflow to power analytics and reporting.
Builds and maintains a petabyte-scale data lakehouse platform for Sberbank, handling batch/streaming data ingestion, ETL pipelines, and data quality controls using Hadoop, Spark, Kafka, and Iceberg/Paimon.
About Xtillion Xtillion is a fast-growing AI solutions firm helping organizations build, operationalize, and scale high-value AI systems. We deliver end-to-end solutions, from design to deployment in real-world…
Design and build enterprise-grade data platforms, pipelines, and warehouses for government clients using Python, AWS, and big-data tools like Spark and Airflow.
Lead marketing analytics projects, build cloud-based ELT pipelines, and create dashboards to optimize campaigns and business integration across markets.
Build and scale ML-powered recommendation systems using Python, TensorFlow/PyTorch, and cloud platforms to personalize user experiences at scale.
Build and maintain scalable data pipelines and AI-ready platforms for next-gen AI products, transforming raw data into trusted assets for analytics and machine learning.
Senior Data Engineer Consultant advises on modern data platforms, AI-native architectures, and enterprise-scale design for a partner company in India, focusing on strategic roadmaps rather than day-to-day development.
Build and scale AI-powered backend systems in Python/AWS, integrating LLMs, retrieval, and agent workflows to serve real users and drive digital wellbeing.
QA Engineer tests and validates cloud platforms, reproducing bugs and automating tests to ensure reliability for open-source and enterprise environments.
Lead a team to design and build scalable GCP-based data pipelines and warehouses using BigQuery, Dataflow, and Airflow to power analytics and reporting for a modern data platform.
Develops end-to-end data pipelines for a natural language search platform, managing multimodal data ingestion, vector/text search preparation, and high-load architecture using Python, SQL, Airflow, Spark, Kubernetes, and S3.
Lead a team of data scientists building and deploying AI-driven models for credit risk, payments, and financial health products at a fast-growing fintech startup.
Design and deliver scalable Databricks Lakehouse architectures for enterprise customers, building prototypes and guiding adoption of data/AI solutions while translating tech into business outcomes.
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