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We're the trusted source for IP address data, handling over 40 billion API requests per month for over 500,000+ users.
Data Engineer – Geolocation Team
Location
United States
Posted
159 days ago
Salary
0
Seniority
Senior
Job Description
Data Engineer – Geolocation Team
IPinfo.io – IP Data Provider
• Design, build, and operate data collection and analysis pipelines • Work with large-scale internet measurement data (we collect 75+ TB per week , including BGP, DNS, ping, and traceroute data from 1200+ global vantage points ) • Research, apply, and implement techniques from cutting-edge internet measurement research • Maintain a high bar for signal quality and defensibility , prioritizing observable network behavior over heuristics or guesswork • Communicate findings clearly by contributing to blog posts, technical documentation, and research publications , both internally and externally
Job Requirements
- Background in one or more of: Internet measurements or network telemetry
- Data engineering or experience with batch, streaming, or real-time data pipelines
- Network engineering or ISP / CDN operations with experience analyzing traffic behavior
- Security research or applied network security
- Threat intelligence or abuse / fraud analysis
- Deep understanding of networking protocols and networked applications (e.g. VPNs, proxies, tunneling, routing behavior)
- Proficiency in Bash scripting, Python, Go , or similar languages for building data collection and analysis systems
- Proficiency in SQL for querying, analyzing, and validating large datasets
- Proficiency with Git and collaborative development workflows (code reviews, pull requests, CI)
- Strong analytical skills and attention to detail; ability to distinguish signal from noise
- Excellent communication skills and ability to clearly explain complex technical findings
- Curiosity and commitment to continuous improvement; belief that systems, signals, and processes can always be improved.
Benefits
- Build at a bootstrapped, independent company with no board or outside investors — we optimize for long-term product quality , not short-term growth targets
- Real ownership and autonomy : you’ll shape systems, signals, and direction, not just implement tickets
- 100% remote , globally distributed team
- Flexible working hours designed for deep focus and a sustainable pace
- Competitive salary , adjusted for experience and local market
- Flexible vacation policy built on trust and personal responsibility
- Solve hard, real-world problems at internet scale , using data most companies never see
- At least one annual company-wide gathering to reconnect and reset in person
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steampunkSteampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology, we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges. As an employee owned company, we focus on investing in our employees to enable them to do the greatest work of their careers – and rewarding them for outstanding contributions to our growth. If you want to learn more about our story, visit Steampunk . We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. Steampunk participates in the E-Verify program.
This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking a Principal Data Solution Architect / Lead Data Architect to serve as the senior-most technical authority for end-to-end data architectures, cloud data platforms, integration strategies, and enterprise-scale modernization initiatives. This role operates at the intersection of architecture, engineering, analytics, AI, and mission strategy. The Principal Data Solution Architect shapes the vision for how data is collected, governed, transformed, stored, accessed, and activated across complex environments—ultimately enabling reliable analytics, ML/AI capabilities, and mission-critical applications. This leader drives architectural strategy across data platforms, lakehouses, warehouses, integration layers, and AI/ML pipelines, while guiding engineering teams toward scalable, secure, and maintainable solutions. Contributions - Serve as the chief architect for data platform modernization, designing enterprise data ecosystems including lakehouse architectures, data mesh/fabric patterns, domain modeling, and multi-cloud data strategies. - Translate mission and business needs into actionable data architecture roadmaps, reference architectures, and solution blueprints. - Architect robust ingestion, transformation, and serving layers using a blend of batch, streaming, CDC, API-based, and event-driven patterns. - Lead end-to-end data modeling strategy, including canonical data models, semantic layers, MDM architectures, metadata systems, and AI/ML-aligned feature modeling. - Partner with Data Engineering, Data Science, AI/ML Engineering, and LLMOps/MLOps teams to ensure data platforms support analytics, ML, RAG systems, and advanced automation use cases. - Define and enforce enterprise data standards: schema evolution, data contracts, quality frameworks, lineage expectations, observability, data zones, and Zero Trust data-access policies. - Drive platform engineering decisions including storage optimization, cluster sizing, compute orchestration, network design, and cost-performance tradeoffs. - Guide selection and adoption of platform technologies such as Databricks, Snowflake, Redshift, Synapse, BigQuery, lakehouse engines, metadata platforms, and orchestration tools. - Oversee architectural governance, including design reviews, performance evaluations, cloud readiness assessments, and alignment with enterprise cybersecurity and compliance requirements. - Serve as a senior advisor to client executives, framing modernization strategies, defining investment pathways, and articulating value realization for enterprise data initiatives. - Mentor Data Engineers, Data Architects, and cross-functional technical staff, strengthening architectural maturity across programs. - Develop reusable frameworks, architectural patterns, playbooks, and internal accelerators that improve consistency and reduce delivery time across engagements. - Stay current with emerging trends in cloud-native data ecosystems, metadata automation, distributed compute, AI-ready data architectures, and federal data regulations. 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