

Intracruit Solutions
Database Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Database Engineer, 100% remote, with a contract length of unspecified duration and a pay rate of "unknown." Requires 3+ years in network data engineering, strong Python skills, and hands-on experience with AI and Splunk.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
February 13, 2026
π - Duration
Unknown
-
ποΈ - Location
Remote
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
United States
-
π§ - Skills detailed
#Network Security #Scala #AI (Artificial Intelligence) #Security #Cloud #Data Extraction #Scripting #Base #Python #AWS (Amazon Web Services) #Data Engineering #React #Splunk #Migration #Automation #Observability #"ETL (Extract #Transform #Load)" #Linux
Role description
100% remote
Database Engineer
USC/GC/GC EAD
We are migrating from legacy network infrastructure to a modern Secure Service Edge (SSE) architecture. This transition unlocks significantly richer telemetry and network data, creating an opportunity to proactively identify, analyze, and resolve user connectivity issues before they escalate.
This role focuses on extracting, interpreting, and correlating network and security data to understand whether an issue is user-specific, application-related, infrastructure-based, or environmental (e.g., data center location, gateway performance, or external factors like weather). The goal is to move from reactive troubleshooting to predictive insight.
You will help design and build an AI-driven agent system that ingests network data, identifies trends, and builds a growing knowledge base to "look around cornersβ and surface root causes quickly when users report issues such as being unable to access a website or service. Key Responsibilities
β’ Support the migration from legacy infrastructure to a single-tenant, single-policy SSE environment
Extract, analyze, and trend network and security telemetry data from multiple systems
β’ Interpret data to determine whether issues stem from users, applications, gateways, DNS, data centers, or external factors
β’ Design and contribute to an AI-driven agent system that proactively analyzes data and builds institutional knowledge
β’ Develop scripts and tooling to pull, normalize, and correlate data across platforms
β’ Build and maintain a knowledge base of recurring issues, patterns, and resolutions
β’ Analyze differences ( "deltaβ) between systems and understand why one performs better than another
β’ Collaborate across network, security, and cloud teams to validate findings and improve observability
Required Skills & Experience
β’ 3+ years of experience in network data engineering, infrastructure, or similar technical roles
β’ At least 1 year of hands-on experience working with AI (someone who can be like ex "Gemini will not be good for this, you want claudβ
β’ Strong scripting and automation skills (Python)
β’ Experience with stored procedures and structured data extraction
β’ Experience with AWS (only 1 of 3 candidates need AWS)
β’ Hands-on experience with Splunk
β’ Linux systems experience
Solid understanding of networking fundamentals, including:
β’ IPv6
β’ DNS (what it is, how it works, and how failures present)
β’ Experience analyzing data within a networked environment (not just application-level logs)
β’ Ability to work across multiple systems and understand their comparative strengths and weaknesses
Nice to Have
β’ Experience with Elastic (training can be provided if not already familiar)
100% remote
Database Engineer
USC/GC/GC EAD
We are migrating from legacy network infrastructure to a modern Secure Service Edge (SSE) architecture. This transition unlocks significantly richer telemetry and network data, creating an opportunity to proactively identify, analyze, and resolve user connectivity issues before they escalate.
This role focuses on extracting, interpreting, and correlating network and security data to understand whether an issue is user-specific, application-related, infrastructure-based, or environmental (e.g., data center location, gateway performance, or external factors like weather). The goal is to move from reactive troubleshooting to predictive insight.
You will help design and build an AI-driven agent system that ingests network data, identifies trends, and builds a growing knowledge base to "look around cornersβ and surface root causes quickly when users report issues such as being unable to access a website or service. Key Responsibilities
β’ Support the migration from legacy infrastructure to a single-tenant, single-policy SSE environment
Extract, analyze, and trend network and security telemetry data from multiple systems
β’ Interpret data to determine whether issues stem from users, applications, gateways, DNS, data centers, or external factors
β’ Design and contribute to an AI-driven agent system that proactively analyzes data and builds institutional knowledge
β’ Develop scripts and tooling to pull, normalize, and correlate data across platforms
β’ Build and maintain a knowledge base of recurring issues, patterns, and resolutions
β’ Analyze differences ( "deltaβ) between systems and understand why one performs better than another
β’ Collaborate across network, security, and cloud teams to validate findings and improve observability
Required Skills & Experience
β’ 3+ years of experience in network data engineering, infrastructure, or similar technical roles
β’ At least 1 year of hands-on experience working with AI (someone who can be like ex "Gemini will not be good for this, you want claudβ
β’ Strong scripting and automation skills (Python)
β’ Experience with stored procedures and structured data extraction
β’ Experience with AWS (only 1 of 3 candidates need AWS)
β’ Hands-on experience with Splunk
β’ Linux systems experience
Solid understanding of networking fundamentals, including:
β’ IPv6
β’ DNS (what it is, how it works, and how failures present)
β’ Experience analyzing data within a networked environment (not just application-level logs)
β’ Ability to work across multiple systems and understand their comparative strengths and weaknesses
Nice to Have
β’ Experience with Elastic (training can be provided if not already familiar)






