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Description:
The Senior Data Engineer will be responsible for building the infrastructure needed for efficient extraction, transformation, and loading of data from various sources such as Hadoop, Spark, and AWS Lambda.
They will design, develop, test, deploy, maintain, and enhance data integration pipelines.
The role involves creating pipeline objects using technologies like Databricks, Apache Spark, Pyspark, Python, and Scala.
Designing and implementing data pipeline architectures using Hadoop, Spark, and related Azure services will be part of the responsibilities.
The Senior Data Engineer will also conduct load and performance testing on data pipelines built with the mentioned technologies.
Requirements:
A Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field is required.
Minimum of 4 years of professional experience in designing and implementing data pipelines in a cloud environment.
At least 2 years of experience in migrating/developing data solutions in the Azure cloud.
1+ years of experience in building/implementing data pipelines using DataBricks.
Proficiency in designing/implementing solutions using databases like Oracle Cloud, Azure, MySQL, and PostgreSQL.
Expertise in using SQL to write complex, optimized queries on large datasets.
Hands-on experience in object-oriented programming with Python.
Professional experience in building real-time data streams using Spark.
Knowledge or experience in architectural best practices for building data lakes.
Preferred experience in creating/maintaining data models.
Benefits:
Competitive hourly rate of $75 - $85.
Inclusive and diverse work environment.
Comprehensive benefits package including healthcare, retirement, life insurance, short/long-term disability, unlimited paid time off, and incentive plans.
Opportunity to work remotely or in a hybrid setup.
Collaborative team environment fostering innovation and creative problem-solving.