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Compunnel, Inc.

Principal Engineering Consultant

Career Insights for Big Data Architect

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What they do

A Big Data Architect develops computer infrastructure and databases needed to process large amounts of data for a company or organization. Identifies big data requirements, supports the implementation of big data platforms and designs, builds and implements database systems. Supports database administration, develops database security policies and works to prevent cyber attacks.

$125,295 / year median in North Carolina

-8% projected decline

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Job Description

plaintext
JOB TITLE
Principal Engineering Consultant
KEY RESPONSIBILITIES
  • Contribute to and keep the industry-leading work of the Unified Agent Platform going
  • Work in with talents across the world in a globally leading firm.
  • State-of-the-art Agentic AI development in a leading professional legal AI firm
  • Implementing AI security, cryptography, and state-of-the-art homomorphic cryptography
  • Being able to understand from the big picture to detailed system implementation of big data and AI retrieval architecture, supporting and innovating as a global platform.
  • Be able to manoeuvre in a very dynamic environment, requires effective communication and social skills.
  • Being able to bridge and communicate across functional teams, locally and globally.
  • Documentation drafting, including architecture, solution comparisons, etc.
  • Have to be dynamically and highly skilled at conducting Proof of Concept systems design in a wide variety of functional domains.
  • To conduct various testing for selection of proper libraries, frameworks
  • To design and implement testing frameworks as guardrails for code delivery quality and behavioral tests.
  • Attending meetings with global teams to liaise and to provide support or systems diagnosis.
  • Rapid learner
  • Communication with key stakeholders and presenting industry-leading solutions in a professional manner
REQUIRED QUALIFICATIONS
  • Hands on Linux/Unix skills
  • Hands on skills on cloud architecture (AWS, Azure, GCP)
  • Robust fundamentals in data architecture and infrastructures, particularly NoSQL (Not only RDBMS, but columnar databases, vector databases, K/V databases, search engines, Aerospike, Clickhouse, ElasticSearch, Solr, ELK, Cassandra, HBase, Cloud-based Spanner, Aurora, DynamoDB, etc.)
  • Solid knowledge in message-driven/event-driven architectures, patterns (Kafka, RabbitMQ, ActiveMQ, SQS, EventBridge, etc.)
  • Solid knowledge in microservice architectures (CQRS, Saga, Composition, Replica, etc.)
  • DevSecOps skills (CI, CD, Jenkins, Kubernetes, Karpenter, CloudFormation, Terraform, IaC, EKS, GKE, SonarQube, etc.)
  • Cloud networking design (L4/L7 load balancers and limitations, DR methodology, rate limiting, performance sizing, binpacking, cloud Kubernetes ingress types, Istio, etc.)
  • Systems and code security (Hashing, deprecation and vulnerabilities, FIPS compliance, etc.)
  • Hands on coding skills with strong fundamentals of computer science, data structures, software and computer architecture (at least 3 languages in previous projects)
  • Knowledge in performance web frameworks for microservices architecture (e.g. Fiber, Gin, Spring Boot, FastAPI, Enterprise J2EE)
  • Knowledge in web serving technologies (e.g. Jetty, Tomcat, Uvicorn, Guvicorn, nginx, Apache HTTPD)
  • Knowledge and exposure in ETL architectures and implementations (Flink, Spark streaming)
  • Strong fundamentals in maintaining clean code, styling, best practices, algorithmic performance, performance and crash-free robust software architectures.
  • Knowledge in end-to-end observability solutions (e.
g. OpenTelemetry, Jaeger, Splunk, Coralogix, structured metrics, Prometheus, Grafana, Datadog, ELK, DTrace)
PREFERRED QUALIFICATIONS
  • Knowledge of Agentic AI and RAG architecture is high advantageous
Preferably:
Go, Rust, Python, C, Java
CERTIFICATIONS
  • Cloud certifications