Join our Team

About This Opportunity
Join Ericsson as a Data Platform / Data Engineer, playing a critical role in shaping our enterprise data ecosystem. You'll design, build, and govern scalable data platforms powering analytics, AI/ML, and business intelligence across the organization — working at the intersection of data engineering, cloud infrastructure, and domain expertise to deliver trusted, high-quality data products.

What You Will Do

• Design and implement enterprise data models using dimensional modeling, Data Vault 2.0, or similar methodologies
• Architect, build, and maintain data warehouses, data lakes, and lakehouse environments on cloud platforms
• Define and enforce data standards, naming conventions, and schema governance across business domains
• Implement end-to-end data governance frameworks — including cataloging, lineage tracking, metadata management, and business glossaries
• Build automated data quality checks and anomaly detection into data pipelines
• Ensure compliance with data privacy regulations through access controls, data classification, and audit practices
• Build and maintain batch and streaming pipelines with full observability, alerting, and change data capture patterns
• Administer and scale cloud data platforms using infrastructure-as-code practices
• Define clear data contracts between producers and consumers; mentor junior data engineers

The skills you bring:

• Expert-level SQL for querying, transformation, and performance tuning
• Strong Python skills for data processing and pipeline automation
• Deep understanding of enterprise data modeling — dimensional modeling, Data Vault 2.0
• Strong grasp of cloud data platform concepts — warehouses, lakes, and lakehouse architectures
• Solid knowledge of data governance, cataloging, lineage tracking, and metadata management
• Understanding of data quality frameworks, privacy regulations, and CI/CD for data pipelines
• Hands on 5+ years of data engineering experience with enterprise data platforms
• Hands-on experience with Snowflake — optimization, cost management, secure sharing, and ELT integration
• Proven experience with data transformation frameworks and workflow orchestration tools
• Experience building batch and streaming pipelines with observability and alerting
• Hands-on experience with data governance and cataloging platforms

Bonus / Nice to Have

• Experience with feature stores for ML models in production
• Familiarity with vector databases and embedding pipelines for RAG
• Exposure to LLM frameworks and AI orchestration workflows
• Experience applying data lineage and audit trails to AI/ML workflows
• Familiarity with telecom data sources — performance counters, KPIs, alarm feeds, network event logs
• Understanding of RAN architecture and 4G/5G data flows
• Experience with high-volume, time-series, and event-driven datasets