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Build and maintain document-automation software for legal claims using Python, Flask/FastAPI, and PostgreSQL; debug and test features under senior guidance.
Build and lead cloud-native FinOps microservices in Python/AWS, owning full lifecycle from design to deployment and scaling.
Build and maintain scalable data pipelines and backend services using Python, PySpark, and AWS to power WinDifferent's marketing automation platform.
Build and maintain scalable, serverless data solutions on Google Cloud, integrating AI tools and engineering best practices for clients in retail, media, and travel.
Build and scale an on-premise Kubernetes-based data platform for a global payments unicorn, blending SRE, data, and ML engineering to support real-time transactions and GenAI services.
Develop and improve the Energy Management System for Greener’s smart battery fleet, using Python and IoT telemetry to analyze reliability issues and implement fixes.
Build and maintain the data platform for a quantitative investment firm, creating Python applications and Airflow pipelines on AWS to process and distribute market data for research and backtesting.
Build and scale Airweave’s distributed data pipelines, vector databases, and LLM inference infrastructure to power thousands of AI agents reliably at scale.
Build and maintain production-grade data pipelines and AI solutions for enterprise clients, using cloud platforms, orchestration tools, and modern data stacks like Snowflake, Databricks, and dbt.
Build and maintain the software that keeps Greener’s smart battery fleet running reliably in the field, using Python, IoT telemetry, and data analysis to spot risks and drive improvements.
Designs and builds scalable, cloud-native data infrastructure on Kubernetes, deploys data applications, and maintains complex data architectures using Docker, Airflow, and cloud platforms.
Build and maintain a data platform for quant research and backtesting using Python, Airflow, and AWS to process market and reference data.
Build and maintain scalable data pipelines and API-first services for ad-tech, using Python, Spark, Kafka, and cloud platforms to ingest, transform, and distribute audience data reliably.
Build and operate scalable data pipelines for ingestion, processing, and distribution in an ad-tech platform, using Python, Spark, Kafka, and cloud services.
Leads Azure data-platform architecture and design for clients, translating business needs into scalable, secure solutions using Azure services like Fabric, Databricks and Purview.
Build and scale a low-latency data platform for cross-border payments using StarRocks, Flink, dbt, and Airflow while leading architecture and mentoring engineers.
Build and maintain a modern data platform on GCP, designing scalable pipelines with Databricks, Spark, and Airflow to power analytics and ML for enterprise teams.
Designs and builds scalable data platforms using Snowflake, Databricks, Kafka, and Airflow on Azure/AWS/GCP, focusing on data lakehouses, real-time streaming, and automated pipelines.
Build and scale a cloud-native data platform using Databricks, Spark, and AWS to power analytics and ML at a data-driven tech company.
Lead hands-on technical role designing scalable Azure data platforms, setting standards, and mentoring engineers for a consultancy serving finance and logistics clients.
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