Senior Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 14%

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Nexus Cognitive

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2018

💼 Consulting

📣 Marketing

📦 Logistics

💰 Series unknown on 2024-07

Consulting • Marketing • Logistics

Nexus Cognitive is a composable intelligence layer and open data platform that sits above enterprise data systems to make data AI-ready without replacing existing infrastructure. It provides a universal query gateway, automatic enrichment, centralized governance, and a managed full‑stack service that enables rapid (30‑day) AI deployments, lower TCO, and enterprise-grade security and compliance. Nexus Cognitive powers revenue, customer, operational, and risk intelligence by unifying data across warehouses, lakehouses, and cloud platforms while preserving business context and minimizing tool sprawl.

📋 Description

• Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and deliver data from internal and external sources • Develop and optimize data models and schemas supporting analytics, reporting, and downstream application needs • Monitor pipeline health, troubleshoot data quality issues, and implement alerting and observability practices • Partner with analytics, product, and engineering teams to translate data needs into durable data solutions • Improve performance, scalability, and cost-efficiency of existing data infrastructure • Write technical documentation and contribute to standards for testing, code review, and deployment • Participate in on-call or incident response rotations as needed to support production data systems

🎯 Requirements

• 4+ years of professional experience in data engineering or a closely related discipline • Strong proficiency in SQL and at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java) • Hands-on experience building and operating ETL/ELT pipelines in a production environment • Experience working with cloud data platforms (e.g., AWS, GCP, or Azure) and modern data warehousing tools • Solid understanding of data modeling, data quality, and pipeline orchestration concepts • Comfort working with large, complex datasets and diagnosing data issues independently • Experience with orchestration tools such as Airflow, Dagster, or similar • Familiarity with streaming data technologies (e.g., Kafka, Kinesis) • Experience with dbt or similar transformation frameworks • Exposure to infrastructure-as-code practices (e.g., Terraform) • Prior experience supporting analytics or data science teams directly

🏖️ Benefits

• A collaborative team culture built on curiosity and respect • Challenging work where your contributions clearly matter • A leadership team that invests in learning and development • Opportunity to work at the intersection of cloud, data, and AI innovation