DataOps

Job Description: As an integral part of the data engineering team, you will be responsible for onboarding various data sources by creating ETL pipelines. You will provide resolutions and/or workarounds to data pipeline related queries/issues as appropriate. Ensuring that ingestion pipelines empowering the lakehouse and data mesh are up and running will be a key part of your role. You will also enable end users of the data ecosystem with query debugging and optimization. Collaboration with different teams to understand and resolve data availability and consistency issues is essential. Your efforts will focus on ensuring that teams consuming data can do so without spending the majority of their time on acquiring, cleaning, and transforming it. Additionally, you will assist other teams in becoming more independent with data analysis and data quality by coaching them with tools and practices. Continuous improvement in technical knowledge and problem-resolution skills will be expected, with a commitment to strive for excellence. You should apply if you have 1-3 years of experience in ETL and data engineering, possess the ability to read and write complex SQL, have prior experience in Python and Spark, are familiar with data modeling, data warehousing, and lakehouse (utilizing Databricks), have experience working on cloud services, preferably AWS, are dedicated to continuous learning and self-improvement, and can effectively collaborate as a team player with strong analytical, communication, and troubleshooting skills. Key Skills: - Databricks - ETL - AWS Preferred Skill: - MySQL - Python,