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Designs and maintains enterprise data architecture, builds scalable data platforms (lakes, warehouses, streaming), and sets standards for modeling, governance, and cloud integration to support analytics and AI.
Designs and maintains MongoDB-based data pipelines and warehouses for banking systems, implementing ETL/ELT to ensure secure, scalable financial data management.
Designs and maintains MongoDB databases and ETL pipelines for banking systems, ensuring secure, scalable data management for financial applications.
Senior Python developer refactors and modernizes production forecasting and data-processing platforms, applying clean-code and data-engineering best practices.
Builds RAG workflows and AI-agent pipelines using Teradata-Claude integrations in Python/SQL, optimizing data models and ETL/ELT for advanced analytics.
Build and maintain scalable data pipelines and AI/ML platforms to create trusted, reusable data products that support analytics and business decision-making.
Build and automate data pipelines, migrate legacy systems to modern platforms, and ensure data accuracy and reliability for a fintech lender.
Designs and builds scalable data pipelines and modern data warehouses using Microsoft Fabric, Azure, and Databricks to enable analytics and reporting.
Design and build scalable data platforms using Microsoft Fabric, Azure Data Factory, and Databricks, including modern data warehouses, lakehouses, and ETL/ELT pipelines.
Designs and maintains data marts in Greenplum/PostgreSQL, writes optimized SQL, builds dashboards in Polymatica, and ensures data quality for a federal social-insurance agency.
Data Engineer building modern data pipelines and warehouses using Microsoft Fabric and Azure for enterprise clients, with a focus on cloud-based AI/ML solutions and ETL/ELT workflows.
Designs and builds scalable GCP data pipelines (batch/streaming) using BigQuery, Dataflow, and Scala/Java/Python to turn raw data into business insights while ensuring security, compliance, and efficiency.
Designs and builds cloud-native data pipelines on Azure, integrating big data tools like Spark and Databricks to feed analytics and ML models for enterprise clients.
Designs and builds cloud-native data pipelines, ELT workflows, and data models for a data lake/warehouse using Python, Java, Spark, and cloud platforms like GCP or Microsoft Fabric.
Builds and deploys production-grade data pipelines in Python/SQL, using Airflow or dbt to turn prototypes into scalable analytics services with FastAPI/Flask APIs.
Build dashboards, data models, and ELT pipelines to turn business questions into reliable data and insights for a fast-growing startup.
Lead a data engineering team to design, build, and optimize AWS-based data pipelines and architectures, ensuring high-quality ETL/ELT processes and data lake solutions.
Design and build cloud-native data platforms using Snowflake, dbt, Airflow, Python, and SQL, integrating Salesforce data for analytics and governance.
Build and maintain ETL/ELT pipelines and translate business needs into scalable data solutions while collaborating with data scientists and cross-functional teams.
Build and maintain scalable ETL/ELT pipelines and lakehouse architectures, design data models, and collaborate with ML/AI teams in a hybrid setup.
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