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Data Operations Engineer
2 months ago
We are seeking a highly skilled and motivated Data Operations Engineer to join our Information Technology team at Fiberlight, LLC. As a Data Operations Engineer, you will play a crucial role in managing, optimizing, and ensuring the smooth operation of our organization's data infrastructure and systems.
Key Responsibilities:- Data Pipeline Management: Design, implement, and maintain efficient data pipelines to ingest, process, and store large volumes of structured and unstructured data from various sources.
- ETL Development: Develop and optimize ETL processes to ensure the smooth and accurate movement of data from source to destination, adhering to best practices and data governance guidelines.
- Data Quality Assurance: Monitor data quality and perform data validation to ensure consistency, accuracy, and completeness of data across the data ecosystem.
- Database Management: Manage and maintain databases and data warehouses, ensuring data availability, security, and integrity.
- Performance Optimization: Identify opportunities to improve data processing performance and implement optimizations to enhance data processing speed and efficiency.
- Troubleshooting and Issue Resolution: Investigate and resolve data-related issues, ensuring timely and effective solutions to maintain data integrity and availability.
- Collaboration and Communication: Collaborate with data engineers, data scientists, and other cross-functional teams to understand data requirements, provide technical expertise, and support data-driven initiatives.
- Automation and Monitoring: Implement monitoring and alerting solutions to proactively identify and address data processing issues and ensure continuous data availability.
- Documentation: Maintain comprehensive documentation of data processes, pipelines, and configurations to facilitate knowledge sharing and support the team.
- Data Security and Compliance: Ensure compliance with data security and privacy policies, implementing necessary measures to safeguard sensitive data.
- Bachelor's or master's degree in computer science, engineering, or equivalent working experience.
- Equivalent proven experience in data engineering, ETL development, and data pipeline management.
- Proficiency in programming languages such as Python, Java, C++, PowerShell.
- Hands-on experience with data warehousing technologies (e.g., SQL Server, PostgreSQL, MySQL / MariaDB).
- Familiarity with big data technologies (e.g., Hadoop,...) and cloud-based data platforms (e.g., AWS, Azure, GCP).
- Strong analytical and problem-solving skills, with an ability to troubleshoot complex data issues.
- Knowledge of data modeling, data governance, and data quality best practices.
- Experience with data visualization tools (e.g., Tableau, Power BI) preferred.
- Demonstrated ability to adapt to new technologies and eagerness to stay updated with industry trends in data management and governance.
- Excellent communication skills and ability to work effectively in a collaborative team environment.
- Operating Systems: Proficiency in operating systems such as Windows, Linux, or macOS, including system administration, file management, and basic command-line operations.
- Networking Concepts: Understanding of networking fundamentals, including IP addressing, subnetting, DNS, DHCP, routing, and network protocols (TCP/IP, HTTP, HTTPS, etc.).
- Hardware Fundamentals: Understanding of computer hardware components, including CPUs, RAM, storage devices, and peripherals.
- Virtualization: Understanding of virtualization technologies such as VMware or Hyper-V, including virtual machine deployment and management.
- Cloud Computing: Basic knowledge of cloud computing platforms like AWS, Azure, or Google Cloud, and an understanding of cloud services such as storage, compute, and networking.
- Troubleshooting Skills: Ability to diagnose and resolve technical issues, both hardware and software-related, and provide effective solutions.
- Documentation and Communication: Strong documentation skills and the ability to communicate technical concepts clearly to both technical and non-technical stakeholders.
- Databases: Familiarity with relational database concepts and SQL querying. Knowledge of common database management systems like MySQL, Oracle, or PostgreSQL.
- Monitoring and Logging: Experience with monitoring tools like ScienceLogic, SolarWinds, Thousand Eyes, Nagios, Zabbix, or Prometheus, and basic logging solutions such as SysLog and technology stacks like ELK stack (Elasticsearch, Logstash, Kibana).
- IT Security: Awareness of information security best practices, including data encryption, access controls, and vulnerability assessment.
- Scripting and Automation: Experience with scripting languages like Python, PowerShell, PERL, or Bash to automate repetitive tasks and processes.
- IT Service Management (ITSM): Basic knowledge of ITSM frameworks such as ITIL, including incident management, change management, and service request processes.
- Web Technologies: Familiarity with web technologies such as HTML, CSS, and JavaScript, and an understanding of web servers (e.g., Apache, Nginx).
- Version Control: Familiarity with version control systems like Git to manage and collaborate on code repositories.
- Must be able to sit, stand, walk, stoop, kneel and reach.
- Must be able to speak, write, read and understand English.
- Must have visual acuity.
- Must be able to lift 0-25 pounds.