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Senior Software Engineer (Data Pipeline)
Posted 3 days agoViewed
💎 Seniority level: Senior, 5-10+ years
💸 Salary: 70000.0 - 80000.0 USD per year
🔍 Industry: Software Development
🏢 Company: Civitas Learning👥 101-250💰 Private about 6 years agoEducationEdTechPredictive Analytics
🗣️ Languages: English
⏳ Experience: 5-10+ years
Requirements:
- 5-10+ years of software or data engineering
- Experience in designing, debugging, and building modern ETL data pipelines
- SQL/SQL Query Tuning
- Python
- Scala
- Java
- Pandas/EMR/Spark
- AWS
- RDBMS (PostgreSQL, SQL Server, Oracle, DB2, etc.)
Responsibilities:
- Build and maintain scalable and performant ETL data pipelines from analysis to production.
- Ability to perform both new feature development and maintenance on all Civitas ETL data pipelines and infrastructure.
- Ability to optimize existing data flow architecture for performance improvement and cost reduction.
- Ability to work across multiple products and engineering teams to resolve customer issues.
- Perform ad hoc query analysis, optimization, and data investigation.
- Lead other talented engineers in software engineering design and best practices with a focus on customer satisfaction.
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🔥 Senior Software Engineer- Data Pipeline
Posted about 2 months ago
📍 United States, Brazil, Tel Aviv
🔍 Cybersecurity
🏢 Company: Axonius👥 600-600💰 $200,000,000 Series E about 1 year agoAsset ManagementCloud SecurityInformation TechnologyCyber SecurityNetwork Security
- 5+ years of hands-on experience in server-side development.
- 2+ years of experience with Python development.
- Experience with No-SQL DBs - preferably MongoDB.
- Experience with Monitoring, Metrics, and Tracing technologies and concepts.
- Knowledge in networking - TCP/IP, common protocols, routing, NAT, etc.
- Good verbal and written communication skills.
- Can do approach.
- Experience with Messaging technologies.
- Experience in the cyber security industry - advantage.
- Design the next generation of the Discovery Cycle by addressing the gaps, needs, and bottlenecks.
- Implement the next generation of Axonius Discovery Cycle while preserving a clean design, high code standards, efficiency, and reliability.
- Constantly monitor the data pipeline performance and make recommendations to enhance system architecture.
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