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Design and implement end-to-end AI solutions using Python, PySpark, Databricks, Postgres and open-source LLMs like Qwen, building data pipelines, RAG systems and AI agents for enterprise clients.
Build and productionize ML models and data services that power real-time credit and fraud decisions for SMEs, using Python, FastAPI, SQL, and AWS.
Lead a team to design and build scalable cloud data platforms and AI infrastructure using Python, PySpark, SQL, and Azure services.
Design and build cloud-native data platforms using Snowflake, dbt, Airflow, Python, and SQL, integrating Salesforce data for analytics and governance.
Builds and secures data pipelines for analytics, using Python, SQL, and orchestration tools like Airflow to ingest and transform data.
Build and scale data pipelines and services for a sustainability-focused AI platform, using SQL, ETL/ELT tools like Airflow, and modern data warehousing to power analytics and decision-making.
Owns a core data domain’s warehouse, defines modeling standards, and builds a semantic layer for AI agents and stakeholders using SQL, dbt, Airflow, and CI/CD.
Builds and automates data pipelines on GCP and Snowflake using DBT, Prefect, and Airflow to deliver analytics for audit teams.
Build and maintain scalable data pipelines in Google Cloud using Airflow, dbt, BigQuery, Pub/Sub, and Snowflake to enable reliable data ingestion, transformation, and analytics.
Lead a remote team of data engineers to build and scale Airalo’s cloud data platform (GCP/BigQuery) and pipelines, turning raw travel data into actionable insights for product and growth decisions.
Lead a Data Engineering team at a global ad-tech DSP, building scalable pipelines, feature stores, and data-quality frameworks to power real-time bidding ML models in a high-growth mobile advertising platform.
Build and maintain a customer identity data pipeline for a large European ecommerce platform using BigQuery, Python, Airflow, and Splink to unify customer records across multiple verticals.
Design and maintain a hybrid cloud data platform (AWS + GCP/BigQuery) for a European fintech, building data lakes, pipelines, IAM, and observability to power analytics and AI transformation.
Build and scale data-driven and generative AI solutions for global clients in banking, pharma, and public sector using cloud platforms, Spark, and Azure OpenAI.
Builds and maintains Snowflake and AWS-based data infrastructure, automates pipelines with Terraform, and ensures secure, scalable analytics across 60+ countries.
Owns and evolves a Snowflake-based data platform and AWS lakehouse, managing Terraform infrastructure and Airflow workflows while collaborating with cross-functional teams.
Build and maintain Java-based data pipelines and APIs on GCP to power open-banking analytics and billing for fintech infrastructure.
Senior Data Engineer builds and maintains ETL pipelines, cloud systems, and RAG-based AI integrations using Python, SQL, Airflow, and Databricks.
Build and migrate scalable data pipelines from Java/Spark to Python, design a corporate Data Lake, and integrate data into MongoDB/PostgreSQL for BI and Data Science teams.
Designs and builds scalable batch and streaming data pipelines in Python, Spark, and ClickHouse, and manages Airflow workflows for scheduling and monitoring.
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