Data Engineer
Develop and optimize data solutions within Snowflake while building and maintaining robust data pipelines. Monitor system performance and collaborate with data engineers and analysts to ensure data security and governance.
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Develop and optimize data solutions within Snowflake while building and maintaining robust data pipelines. Monitor system performance and collaborate with data engineers and analysts to ensure data security and governance.
You will be responsible for designing, building, and maintaining scalable data processing pipelines and integration mechanisms. Additionally, you will contribute to architectural decisions, define engineering standards, and ensure high data quality and reliability across the platform.
Develop, test, and maintain robust data pipelines to process AST outputs, knowledge graph structures, and vector embeddings. Collaborate with engineering teams to normalize code dependency graphs and optimize data retrieval speeds.
The Data Engineer will develop, maintain, and monitor robust data pipelines to process AST outputs, knowledge graph structures, and vector embeddings. They will also collaborate with AI/ML engineers to normalize data and ensure consistency across pipeline runs.
The Data Engineer will develop, maintain, and monitor robust data pipelines to process AST outputs, knowledge graph structures, and vector embeddings. They will also collaborate with AI/ML engineers to normalize data and ensure consistency across pipeline runs.
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Own and scale the central database and knowledge graph that serves as the memory for AI agents and product features. Design ingestion pipelines for funding rounds and market news while ensuring end-to-end data quality and entity resolution.
Design, build, and optimize scalable data processing systems and ETL/ELT pipelines in cloud and on-prem environments. Support the migration of legacy DWH systems and implement monitoring and alerting for data processes within an Agile framework.
Design, build, and operate batch and real-time data pipelines using Azure, Databricks, and Python. The role involves developing data solutions for either the Data Science team for ML forecasting or the Data Streaming Platform team for real-time data scaling.
Design, build, and operate batch and real-time data pipelines using Azure, Databricks, and Python. Collaborate with cross-functional teams to enable forecasting, analytics, and ML-based intelligence through scalable data solutions.
You will lead the design, development, and operation of scalable data products and pipelines on the Enterprise Data Platform. Additionally, you will mentor a team of data engineers and champion engineering best practices to drive data-driven decision-making.
Maintain and enhance existing data processes to ensure reliability, scalability, and performance optimization. Drive modernization initiatives across the data platform while collaborating with product engineering teams on technical solutions.
The Senior Data Engineer will maintain and enhance scalable data processes while driving modernization initiatives across the data platform. They will collaborate with cross-functional teams to optimize data pipelines, improve query performance, and ensure system reliability.
Maintain and enhance existing data processes to ensure reliability, scalability, and performance optimization. Collaborate with product engineering teams to design large-scale data pipelines and drive modernization initiatives across the data platform.
The Senior Data Engineer will maintain and enhance scalable data processes while driving modernization initiatives across the platform. They will collaborate with cross-functional teams to optimize data pipelines, improve query performance, and ensure system reliability.
The role involves maintaining and enhancing scalable data pipelines while driving modernization initiatives across the data platform. You will collaborate with cross-functional teams to optimize data models and improve system performance for cybersecurity applications.
Design and develop high-volume batch and streaming data ingestion pipelines across AWS and GCP platforms. Lead and mentor junior engineers while collaborating with cross-functional teams to build new product features.
The Lead Data Engineer will design, develop, and maintain robust Spark applications while enforcing coding standards and best practices across the project. They will also collaborate with cross-functional teams to optimize performance and ensure the reliability of enterprise-level data solutions.
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The Data Engineer will design, develop, and optimize scalable ETL/ELT processes and data solutions within Google BigQuery. They are responsible for ensuring data consistency, reliability, and auditability across financial and operational reporting domains.
Maintain and enhance existing data processes while driving system reliability and performance improvements. Collaborate cross-functionally to modernize data workflows and ensure architectural alignment.
Migrate data products and analytical workloads from legacy systems to a modern cloud data platform. Build and maintain scalable batch data pipelines while ensuring data quality and performance optimization.
You will design, develop, and maintain scalable batch and real-time data pipelines using Python, SQL, and dbt. Additionally, you will manage cloud-based data infrastructure on AWS and collaborate with cross-functional teams to deliver robust data solutions.
The candidate will develop and maintain data pipelines and Lakehouse architectures using Azure Databricks, PySpark, and Azure Data Factory. They will also support existing SQL Server data platforms and collaborate with BI teams to ensure data quality and performance.
Design and develop scalable ETL/ELT pipelines and data transformations using Snowflake and Python. Collaborate with cross-functional teams to ensure data quality, performance, and reliability across data solutions.
The Integration Engineer will design, build, and maintain scalable data flows and integration pipelines across enterprise systems including ERP, HRIS, and FinOps platforms. They will also implement automation scripts, manage CI/CD processes, and ensure system reliability through monitoring and observability.
Provide technical leadership to a team of data engineers while designing and building scalable data pipelines and products on Snowflake. Collaborate with BI and data governance teams to migrate business logic and ensure high data quality standards.
You will design, build, and maintain scalable data pipelines while supporting migrations to BigQuery. Additionally, you will orchestrate and optimize data processing workloads to deliver production-grade data products for analytics and business intelligence.
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The Senior Data Engineer will design and maintain large-scale cloud data infrastructure, including efficient pipelines and microservices. They will collaborate with product owners to organize disparate data sources and optimize performance for healthcare applications.
Develop and maintain scalable data pipelines using SQL-based ELT patterns and optimize transformation logic for curated data marts. Ensure data quality through rigorous testing, orchestration with Airflow, and effective schema evolution using CI/CD practices.
Develop and maintain scalable data pipelines using SQL-based ELT patterns and optimize transformation logic for curated data marts. Ensure data quality through rigorous testing, orchestration with Airflow, and effective schema evolution using CI/CD practices.
Design and develop high-volume batch and streaming data ingestion pipelines across AWS and GCP platforms. Lead and mentor junior engineers while collaborating with cross-functional teams to build new product features.
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