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Designs, builds, and maintains scalable data pipelines and ETL/ELT workflows using Airflow, Snowflake, and ERP APIs to automate data integration and enable AI-driven analytics.
The Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines, databases, and analytics platforms that support cloud-based digital applications for food and beverage processing…
Build cloud-native data platforms and MLOps workflows, designing ETL/ELT pipelines, data lakes/warehouses, and feature stores for AI/ML and analytics.
Build and optimize ETL/ELT pipelines to move and transform data between Snowflake, Salesforce, SAP and other corporate systems using Informatica Cloud and Python.
Builds and maintains data pipelines, integrates internal/external sources, and ensures data quality and availability using SQL, ETL/ELT tools, and batch/event processing.
Build and optimize data pipelines using Databricks, PySpark, and SQL to create a data lakehouse architecture for Trade Marketing analytics.
Senior Data Engineer builds and maintains scalable data pipelines and a semantic layer to power BI, AI, and operations across 60+ brands.
Design and build scalable data pipelines and infrastructure using SQL, Python, Databricks, dbt, and AWS Redshift to enable production-ready analytics and AI solutions.
Build and maintain scalable data pipelines and cloud infrastructure in GCP to support analytics, ML, and real-time personalization at a large retail company.
Build and maintain scalable data pipelines, ETL processes, and data warehouses using cloud tools like AWS and Python, while collaborating with cross-functional teams to deliver data-driven products.
Build and maintain scalable data pipelines, ETL processes, and data warehouses using cloud tools (AWS, Azure, GCP) and SQL/Python to integrate and clean data for analytics.
Build and maintain data pipelines, ETL workflows, and dashboards to support AI product analytics and evaluation using SQL, Python, and modern data warehouses.
Build and own a structured research data platform for investment teams, ingesting and parsing documents (PDF, HTML, XBRL) and deploying LLM-powered query APIs on cloud data warehouses.
Key Responsibilities Design, develop, and optimize scalable ETL/ELT pipelines to ingest, transform, and integrate data from multiple source systems. Build and maintain cloud-based data platforms, data lakes, and data…
Designs and builds ETL/ELT pipelines, REST APIs, and web apps using Google Cloud, BigQuery, Airflow, Python, .NET, and React.
QA role ensuring data quality for investment-banking platforms built on Databricks, Azure and Spark, designing tests for ETL/ELT pipelines and validating data transformations.
Builds and maintains data pipelines, REST APIs, and web apps using GCP, BigQuery, .NET, Python, and React, with ETL/ELT and Cloud Composer workflows.
Design and build scalable data pipelines, warehouses, and lakes using Python, SQL, Spark, and cloud platforms to power analytics and decision-making.
Build and maintain cloud cost visibility pipelines and datasets using SQL, Python, AWS/GCP, and Snowflake to power cost-aware decisions for Product, Engineering, and Finance teams.
Leads data-architecture projects for banks and insurers, building cloud-native data platforms, pipelines, and governance while managing teams and advising clients on data modernization and MLOps.
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