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Lead Data Engineer
Lead a data engineering team to build and maintain robust pipelines and warehouses for a healthcare search engine used in hospitals, primarily using Python, Prefect, and SQL.
Core Data Engineer
Build and maintain core financial data pipelines (Security Master, ETF compositions, market data) using Python, SQL, Airflow, Kafka, and GCP to ensure high-quality, reliable data for quantitative trading.
Data Engineer
Build and maintain data pipelines, optimize T-SQL queries, and automate workflows with Python and Airflow for a banking data warehouse.
Data Engineer
Build and maintain a Databricks-based data platform on Azure, migrating legacy systems and developing PySpark/Airflow pipelines for reliable, scalable financial data pipelines.
Data Engineer
Build and maintain cloud-based data infrastructure for clients, designing scalable pipelines with tools like Spark, Airflow, and Terraform to enable AI-driven solutions.
Data engineer
Build and scale a new data warehouse and pipelines for a fast-growing fintech, using SQL, Python, AWS, and Terraform to enable analytics and real-time decision-making.
Data Engineering
Build and maintain scalable data platforms using Python, Spark, Kafka, and cloud-native tools, then embed with partner orgs to deploy ML models and analytics in production.
Data Engineer
Design and build scalable cloud data pipelines and AI-ready architectures using Azure services to turn raw data into reliable, analytics-ready datasets for ML and decision-making.
Data Engineer
Build and maintain a scalable data warehouse for a national pharmacy group, integrating external sources with Python, Airflow, and PostgreSQL to power internal dashboards.
Data Engineer
Build and maintain data pipelines in Python and SQL to feed analytical systems for environmental and transport oversight, using PostgreSQL, Airflow, and modern data stack tools.
Data engineer
Build and optimize scalable data pipelines using Spark, Airflow, Databricks, and cloud-native tools on Azure/AWS to enable advanced analytics for enterprise clients.
Data Engineer
Build and maintain scalable data pipelines and cloud infrastructure to deliver high-quality, reliable data for analytics, ML, and business processes for government and enterprise clients.
Data Engineer
Build and optimize data pipelines and platforms (Azure, Databricks, dbt) for clients, using Python, SQL, Spark and ELT/ETL patterns to enable analytics and AI.
Data Engineer
Build and maintain scalable data infrastructure using tools like Airflow, Spark, and cloud platforms, while collaborating with client teams to design robust data systems.
Data Engineer
Build and optimize a global data platform serving tens of millions using Python, Airflow, Kafka, and Kubernetes to improve performance, cost, and data quality.
Data Engineer
Build and maintain data pipelines in Python and SQL to integrate and clean datasets for environmental and transport regulators, using PostgreSQL, Airflow, and DuckDB.
Senior Data Engineer - Market Data & Reporting Pipelines
Build and maintain Airflow-based data pipelines and reporting workflows for financial market data in a cloud-native Python/SQL environment.
Data Engineer
Build and maintain data pipelines and ML models in Azure to power flight operations and analytics at a European low-cost airline.
Data Engineer
Build and maintain cloud-based data pipelines and transformations using SQL, Python, and tools like Snowflake or Databricks to power analytics and automation for clients in mobility, energy, and finance.
Data Engineer
Build cloud-native data infrastructure that powers AI/ML features for a cybersecurity product, designing scalable pipelines and ensuring reliable data flows from source to model.