Skills: Proficiency in Apache Spark for distributed data processing and analytics. Strong knowledge of OLAP (Online Analytical Processing) techniques for queryinglarge, multi-dimensional datasets. Experience with Time Series Databases such as InfluxDB or TimescaleDB forstoring and querying time-stamped data. Proficiency in SQL and database management systems like PostgreSQL. Knowledge of Data Modeling and schema design for efficient data storage andretrieval. Programming skills in Python or C# for building data pipelines and ETL (Extract,Transform, Load) processes. Excellent problem-solving skills and ability to troubleshoot and optimize datapipelines. Responsibilities: Design, build, and maintain data pipelines using Spark for distributed data processingand analytics. Develop OLAP cubes and data models for efficient querying and analysis of large,multi-dimensional datasets. Build and maintain Time Series Databases for storing and querying time-stampeddata. Optimize database schema design and indexing for efficient data storage andretrieval. Write and maintain SQL queries and stored procedures for data access andmanipulation. Develop and maintain ETL processes for ingesting, transforming, and loading datafrom various sources. Collaborate with Performance Engineers and Simulation Engineers to support theirdata needs and enable data-driven decision making. Monitor and optimize data pipelines and database performance to ensure highavailability and reliability.











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