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About the role
Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience.
The Data QE team is responsible for the quality of data, data services, and data components across our cloud and hybrid cloud environments. We develop tools, create fully automated regression suites and conduct performance tests for distributed data components at cloud scale. If you thrive on solving difficult problems, complex test scenarios, and developing high-performance QE tooling and automation, we would love to discuss our career opportunities with you.
What s in it for you
Performance engineering team is responsible for optimizing the performance and efficiency of software applications, systems, and infrastructure. They play a critical role in ensuring that applications can handle the scale and the systems provide a seamless user experience. By conducting performance testing, analysis, and optimization, they contribute to the overall success and reliability of software systems.
What you will be doing
Required skills and experience
Education
Job ID: 114284345
Skills:
Git, Spark, Python Programming, Data Modeling, Databricks, Advanced Sql, Building scalable ETL pipelines, Data warehousing and BI tools integration
Skills:
Tensorflow, Pytorch, Docker, Oracle, Python, AWS, Sql, Cuda, Git, Gcp, Neo4j, Keras, Azure, AWS Bedrock, NVIDIA, Google Gemini, Transformer architecture, Mistral, Vertex AI, Diffusion models, Agentic workflows, Graph DBs, GANs, LLaMA 3.0, Copilot, OpenAI GPT-3.5
Skills:
Machine Learning, scrapy, Sql, Nosql, Pandas, Numpy, Gcp, Spark, Azure, Python, AWS, scikit-learn, Ai, Analytics, R, BERT
Skills:
Git, BI, Apache Spark, Databricks, Python, Sql, ELT, Etl, Ai
Skills:
snowflake , Mqtt, Kafka, Sql, Tensorflow, Spark Streaming, Pandas, Pytorch, XGBoost, Databricks, Python, Airflow, Scikit-learn, MLflow, Flink, dbt, Kubeflow, AWS Kinesis