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Build and maintain reliable data pipelines and models for analytics, using SQL, PL/SQL, T-SQL, and cloud data warehouses to transform raw data into trusted business insights.
Build and maintain automated data pipelines in Python and GCP, cleaning and validating large datasets while integrating Google Sheets, BigQuery, and APIs.
Build and maintain scalable data pipelines and cloud architectures to ingest, transform, and serve reliable data for analytics and reporting across hybrid environments.
Build and maintain data pipelines and microservices on OpenShift, using SQL and Oracle/PostgreSQL to support banking-sector clients.
Build and own the data foundation: reliably land source data into Snowflake, process it on Databricks, and instrument clean product telemetry so data scientists can trust and use it.
Designs and maintains data pipelines using Microsoft Fabric and Azure tools to build scalable analytics platforms for enterprise clients.
Build and maintain scalable data pipelines and cloud infrastructure to move raw client data into clean, secure warehouses for BI and future AI/ML use.
Design and build data pipelines and backend services for AI-driven energy asset operations, integrating SCADA and corporate data in Microsoft Fabric and Power BI.
Build observability platforms using Datadog and OpenTelemetry, instrument apps for metrics/logging, and create dashboards to help teams make data-driven decisions.
Build and maintain ETL pipelines, optimize MongoDB schemas, and create Metabase dashboards to power AI-driven travel rental analytics and reporting.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and optimize data workflows for enterprise clients.
Build and maintain a modern data platform in AWS/Snowflake, designing pipelines with Python/SQL and orchestrating with Airflow/Dagster to power analytics and reporting for a crypto-fintech platform.
Designs and maintains scalable data pipelines, ETL/ELT processes, and cloud-based data platforms to support analytics and AI in high-security sectors like defense.
Build and maintain scalable data pipelines using cloud platforms (AWS/Azure/GCP), Databricks, and tools like Spark and DBT to integrate and transform data for clients.
Build end-to-end data pipelines and analytics solutions for Oysho’s eCommerce platform using Databricks, PySpark, SQL, and Power BI to drive business decisions.
Build and maintain scalable data pipelines and models for a mobile-gaming company, enabling analytics and AI-driven workflows with Python, SQL, and cloud warehouses like Snowflake.
Senior Data Engineer to design and build a greenfield data infrastructure for AI-driven growth, including pipelines, warehousing, and analytics for product, CRM, finance, and marketing teams.
Build and run the AIOps platform that keeps AI models, LLM pipelines, and agents reliable, scalable, and cost-efficient in AWS/Azure.
Build and maintain data pipelines, warehouses, and lakes for Emburse’s SaaS products using Snowflake, Databricks/Spark, AWS, and Looker.
Build and scale data pipelines, warehouses, and analytics to power a fast-growing second-hand marketplace, analyzing pricing, supply, and conversion to drive business decisions.
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