Join our Team
About The Role
We are looking for an experienced Senior Data Engineer to design and operate enterprise-grade data infrastructure — including warehouses, lakes, and marts — while ensuring data quality, governance, and compliance. You will bring deep expertise in data architecture and modeling, combined with proficiency in pipeline orchestration and analytics tooling.
Key Responsibilities
Data Architecture & Modeling
- Design enterprise data models using dimensional modeling, Data Vault 2.0, or similar methodologies
- Architect and maintain data warehouses, data lakes, and lakehouse environments
- Define and enforce data standards, naming conventions, and schema governance across domains
Data Governance & Quality
- Implement data governance frameworks including cataloging, lineage tracking, and metadata management
- Build automated data quality checks, validation rules, and anomaly detection into pipelines
- Ensure compliance with data privacy regulations through access controls and data classification
- Maintain master data management standards, data dictionaries, and business glossaries
Pipeline Engineering & Platform
- Build and maintain batch and streaming data pipelines with full observability and alerting
- Implement change data capture patterns, real-time ingestion, and ELT/ETL frameworks
- Administer and scale cloud data platforms; optimize storage, compute, and cost efficiency
- Manage data infrastructure using infrastructure-as-code practices
Collaboration
- Partner with analytics engineers, data scientists, and BI teams to deliver trusted data products
- Define data contracts between producers and consumers; mentor junior engineers
Required Qualifications
- 5+ years of data engineering experience with a focus on enterprise data platforms
- Expert SQL skills; strong Python for data processing and automation
- Deep experience with cloud data warehouse platforms
- Hands-on experience with data transformation frameworks and workflow orchestration tools
- Experience with data governance and cataloging platforms
- Solid understanding of data quality frameworks, privacy regulations, and CI/CD for pipelines
NICE TO HAVE
AI & Machine Learning
- Experience building and maintaining feature stores to serve ML models in production
- Familiarity with vector databases and embedding pipelines for retrieval-augmented generation
- Exposure to LLM application frameworks and AI orchestration workflows
- Data lineage and audit trails applied to AI/ML workflows for compliance and reproducibility
Telecom & RAN
- Understanding of RAN architecture, including network nodes, interfaces, and data flows across 4G/5G environments
- Familiarity with telecom data sources such as performance counters, KPIs, alarm feeds, and network event logs
- Experience with high-volume, time-series network data and applying data engineering principles to telecom datasets
- Ability to collaborate with network engineers and RAN teams to define data requirements and support analytics use cases
Why join EricssonAt Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world's toughest problems. You´ll be challenged, but you won't be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What happens once you applyClick Here to find all you need to know about what our typical hiring process looks like.Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more.
Primary country and city: India (IN) ||
Req ID: 782132
