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Designs and builds scalable cloud data pipelines, warehouses, and analytics platforms using Python, SQL, Spark, and cloud tools like BigQuery and Snowflake, with optional Gen AI integration.
Lead a team to design and build scalable data pipelines using Azure Databricks, ADF, and PySpark, while integrating with AWS, Snowflake, and BigQuery in hybrid/multi-cloud environments.
Design and build real-time streaming pipelines and integrate generative AI with enterprise data platforms using GCP tools like BigQuery and Pub/Sub.
Builds and maintains PySpark data pipelines on GCP, using BigQuery and Dataproc to process large datasets with Python and SQL.
Build and maintain GCP-based data pipelines and warehouses using BigQuery, Composer, Python, and SQL to integrate and transform diverse data sources.
Senior Data Engineer builds and maintains GCP-based data pipelines, ETL workflows, and analytics models for MSP customers, using Python, SQL, and Airflow.
Build and maintain scalable data pipelines and cloud infrastructure (GCP/AWS/Azure) to process large datasets, using SQL and Python for ETL and data quality monitoring.
Designs and maintains scalable data pipelines and warehouses, transforming raw data into insights for decision-making using Python, SQL, and cloud platforms.
Design and build cloud-based data pipelines and AI analytics platforms for clients, using tools like Snowflake, AWS Redshift, and Apache Airflow to ingest, process, and transform data at scale.
Designs and builds scalable GCP-based data pipelines using Dataflow, Pub/Sub, and BigQuery to ingest, process, and store batch and streaming data reliably.
Build and maintain Plain’s data warehouse and core models using SQL, BigQuery, and dbt/Dataform to ensure reliable analytics for decision-making.
Senior Data Engineer builds and maintains a scalable Medallion Architecture on GCP, using BigQuery, dbt, Fivetran, and Looker to turn raw data into reliable, business-ready insights for an HMO.
Designs and maintains scalable data pipelines using Snowflake, dbt, Airflow, and AWS to power enterprise analytics platforms.
Build and maintain central data-visualization dashboards and collaborate with teams to standardize metrics and design ETL pipelines using SQL, Python, and Google Cloud tools.
Builds and maintains ELT/ETL pipelines and data marts for a retail analytics platform, transforming OLTP data into governed, business-ready datasets for reporting and forecasting.
Build and maintain GCP-based data pipelines and analytics for enterprise clients, using Python, SQL, Airflow, and BigQuery to ensure reliable data ingestion and reporting.
Build and maintain scalable data pipelines and warehouses using BigQuery, ClickHouse, Airflow, Kafka, and CDC tools to power analytics and reporting.
Build and maintain scalable data pipelines and cloud infrastructure on GCP/AWS/Azure to process large datasets, using Python, SQL, and big-data tools like Spark and Airflow.
Build and scale the core backend platform that powers Axle Health’s AI-driven scheduling and workforce management software for in-home healthcare providers.
About Us Axle Health builds AI scheduling and workforce management software to empower in-home healthcare providers to deliver exceptional, personalized care right where patients feel most comfortable—at home. Some of…
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