About this opportunity:
As a Data Engineer in the HWM Data Management & Visualization team, you will play a key role in designing, developing, and maintaining scalable data solutions that support Ericsson's Hardware Management and Lab Operations ecosystem.
You will be responsible for building reliable data pipelines, integrating multiple enterprise data sources, managing data models, and ensuring high-quality, secure, and accessible data for analytics, reporting, automation, and AI-driven initiatives.
The Data Engineer works closely with Product Owners, Business Analysts, Data Scientists, Data Architects, Visualization Engineers, and operational stakeholders to transform raw operational data into trusted and governed data products that enable business decisions, process optimization, and digital transformation.
What you will do:
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Design, build, and maintain scalable data pipelines, ETL/ELT processes, and integrations across enterprise systems, databases, APIs, and cloud or hybrid platforms.
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Develop and manage data models, data marts, warehouses, and lakehouse-ready structures that support reporting, analytics, automation, AI, and machine learning use cases.
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Ensure data quality, integrity, governance, and master data standards through automated monitoring, validation, reconciliation, and control mechanisms.
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Deliver trusted, reusable, and well-documented datasets that enable business intelligence, self-service analytics, operational reporting, and advanced analytics.
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Optimize data platform performance through partitioning, indexing, query tuning, storage optimization, and scalable infrastructure design.
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Collaborate with architects, analysts, data scientists, and business stakeholders to translate requirements into secure, sustainable, and fit-for-purpose data solutions.
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Implement and govern security, compliance, and access management controls, ensuring adherence to enterprise information security, privacy, audit, and regulatory requirements.
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Drive continuous improvement through automation, modernization, migration initiatives, structured deployment practices, version control, troubleshooting, and operational excellence.
The skills you bring:
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Proficiency in Python, SQL, and Shell/BASH scripting.
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Experience with PostgreSQL, MySQL, Microsoft SQL Server, and Oracle.
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Knowledge of data modelling, normalization, dimensional modelling, and star schema design.
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Experience building ETL/ELT pipelines and workflows.
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Familiarity with REST APIs, JSON, XML, and data integration patterns.
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Experience with Linux/Unix environments.
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Knowledge of Git and version control.
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Understanding of data warehousing and modern data platforms.
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Experience with cloud-based or hybrid data environments.
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Understanding of data lake, warehouse, and lakehouse architectures.
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Analytics & Visualization Enablement
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Data Governance & Security
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Analytical, problem-solving, and stakeholder communication skills
Preferred experience
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Experience with GPU clusters or high-performance compute infrastructure for data preparation and AI workloads.
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Exposure to Azure Data Services, data gateways, database optimization, and reporting ecosystems.
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Experience supporting enterprise reporting and visualization, especially Power BI.
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Experience with agile product and delivery teams.
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Understanding of operational data for utilization, capacity planning, lifecycle tracking, procurement, asset accountability, and compliance reporting.
