Data Operations & Database Engineer

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profile Job Location:

Wayne, PA - USA

profile Monthly Salary: Not Disclosed
Posted on: 2 hours ago
Vacancies: 1 Vacancy

Job Summary

Job Responsibilities:

Data Operations & Database Engineer will be responsible for ensuring the smooth operation deployment and optimization of data pipelines and database systems. They will serve as a trusted advisor to data engineers and architects contributing to the design and implementation of scalable efficient and secure data solutions.

This role requires a strong foundation in SQL ETL processes and cloud data platforms along with a proactive mindset for identifying and resolving data bottlenecks and inefficiencies.

Key Responsibilities

  • Data Operations
    • Design and monitor robust ETL/ELT pipelines.
    • Monitor data quality pipeline health and system performance.
    • Troubleshoot and resolve data processing issues quickly and effectively.
  • Database Administration
    • Manage and optimize databases.
    • Ensure high availability backup and disaster recovery strategies.
    • Implement and maintain security policies access controls and auditing.
    • Perform performance tuning indexing and query optimization.
    • Support schema design and data modeling efforts.
    • Executing ad-hoc data cleanup and corrections.
  • Collaboration & Advisory
    • Partner with data engineers analysts and architects to design scalable data solutions.
    • Provide guidance on best practices for data architecture storage and processing.
    • Identify and resolve data infrastructure bottlenecks and inefficiencies.
    • Contribute to documentation standards and knowledge sharing across the team.

Job Responsibilities: Data Operations & Database Engineer will be responsible for ensuring the smooth operation deployment and optimization of data pipelines and database systems. They will serve as a trusted advisor to data engineers and architects contributing to the design and implementation of s...
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Key Skills

  • Apache Hive
  • S3
  • Hadoop
  • Redshift
  • Spark
  • AWS
  • Apache Pig
  • NoSQL
  • Big Data
  • Data Warehouse
  • Kafka
  • Scala