Senior Data Systems Engineer

2 days ago

Dallas, Texas, United States Shtudy Full time
Job Title: Senior Data Systems Engineer

We are seeking a highly skilled Senior Data Systems Engineer to join our dynamic team at Shtudy. This role requires a strong background in data engineering, cloud technologies, and quality assurance.

Key Responsibilities:
  • Automate ETL pipelines using Python to streamline data integration, transformation, and migration processes.
  • Utilize AWS cloud technologies, including S3, Athena, EMR, Glue, Redshift, Kinesis, and SageMaker, to build robust data infrastructure.
  • Collaborate with cross-functional teams to ensure data architecture and pipelines are scalable, efficient, and robust.
  • Develop, test, and maintain ETL processes in both cloud and on-prem environments using tools such as AWS Glue, Informatica, Ab Initio, or Alteryx.
  • Lead data migration efforts from on-premise to cloud environments, ensuring data integrity and consistency.
  • Perform data analytics, integration testing, and data quality validation within project timelines and budgets.
  • Implement DevOps/DataOps practices, including CI/CD pipelines for data integration and testing workflows.
  • Write complex SQL queries and utilize Unix/Linux scripting to manipulate and analyze data effectively.
  • Support machine learning teams with data preparation and model deployment on platforms such as SageMaker or H2O.
  • Apply best practices for ETL testing strategies, including the creation and execution of test plans and automated testing frameworks.
Mandatory Skills & Qualifications:
  • 11-12+ years of experience in data engineering, with substantial exposure to cloud technologies (preferably AWS) and data quality assurance.
  • Proficiency in Python for automating ETL processes, data integration, and scripting.
  • Extensive hands-on experience with AWS services such as S3, Athena, EMR, Glue, Redshift, Kinesis, and SageMaker.
  • Expertise in SQL and Unix/Linux for data querying, scripting, and troubleshooting.
  • Experience in ETL automation across cloud and on-prem environments using tools like AWS Glue, Informatica, Ab Initio, and Alteryx.
  • Proven expertise in data migration from on-premise to cloud platforms.
  • Strong background in DevOps/DataOps environments, particularly in developing CI/CD pipelines for data engineering.
  • Skilled in data modeling, data warehousing, and data integration strategies.
  • Experience in data analytics and interpreting data from multiple sources for integration.
  • Knowledge of ETL testing strategies and best practices to ensure data integrity and quality.
Preferred Additional Skills:
  • Familiarity with machine learning frameworks such as SageMaker, Machine Learning Studio, or H2O for predictive models and insights.
  • Knowledge of Agile methodologies and experience working in fast-paced, collaborative environments.
  • Experience in creating and managing automated test scripts and frameworks for ETL processes.
  • Expertise in managing and troubleshooting data pipelines in large-scale distributed environments.
  • Strong communication skills and ability to work collaboratively with cross-functional teams.
Education:
  • Bachelor's degree or higher in Computer Science, Data Engineering, Information Technology, or a related field.

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