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Open nowPosted 30 hours agoWe saw it 23 min after it went up

Performance Management / Data Mediation Engineer - 20125

Arbetsförmedlingen (Platsbanken)42,608 open roles

Where
Stockholm, Stockholms län, Sweden
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Your applicationOpen nowPerformance Management / Data Mediation Engineer - 20125Arbetsförmedlingen (Platsbanken) · Stockholm, Stockholms län, Sweden

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The clock on this job

Early applications get read.

10.5% of postings close within 7 days. Measured by our own scanner across the market. Arbetsförmedlingen (Platsbanken) postings stay open a median of 8 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.3%3 days
  3. 10.5%7 days
  4. 15.9%14 days
  5. 34.1%30 days
This job: posted 30 hours ago

Arbetsförmedlingen (Platsbanken) median: 8 days open

The posting

Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry. Job Overview Role Summary An experienced Performance Management / Data Mediation Engineer is needed for a consulting assignment focused on developing and maintaining data pipelines for performance data in a complex network and OSS environment. The role is responsible for building robust, scalable flows for collecting, transforming, and making performance data available from network elements and adjacent systems. The resulting data must be reliable, traceable, and usable for both operational monitoring and analytical purposes. You will work across multiple data sources and integration patterns, contributing to the continued development of in-house capabilities, onboarding new data sources, and improving existing data models and flows. A key objective is to reduce dependency on external vendors by developing and maintaining internal solutions. Key Responsibilities Develop, operate, maintain, and enhance data pipelines for network performance data. Collect, transform, validate, and expose data from network elements and surrounding systems. Implement integrations using protocols and patterns including SNMP, traps, REST APIs, file-based transfers, and streaming telemetry. Ensure data reliability, traceability, quality, lineage, governance, and appropriate schema design. Integrate performance-data solutions with adjacent inventory, topology, ITSM, and analytics systems. Onboard new data sources and further develop existing data models, integrations, and operational flows. Collaborate closely with architects, Product Owners, Scrum Masters, and performance analysts to prioritize improvements and evolve the solution. Contribute to knowledge transfer and the development of internal engineering capability.

Technical Stack & Requirements Strong practical experience with Python, SQL, and ETL/ELT-based data processing. Experience with data-pipeline scheduling and job orchestration. Solid understanding of SNMP, MIBs, polling, traps, and streaming telemetry. Experience with data quality, data lineage, data governance, and schema development. Good understanding of DevOps principles and modern development and operations practices. Experience with performance-management platforms such as OpenText NNMi/NOM, OPTIC Data Lake, or equivalent platforms is advantageous. Experience with messaging technologies such as Kafka, MQ, or similar message buses is advantageous. Experience with time-series and observability tooling such as Grafana, Prometheus, or the ELK Stack is advantageous.

Qualifications & Experience Documented experience designing and maintaining data pipelines within OSS, telecommunications performance management, or related network analytics environments is required. The ideal candidate combines data-engineering expertise with a practical understanding of network data collection and mediation. Fluent English communication skills are required. Additional Nordic or Baltic language skills are considered advantageous.

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