
1001 - 5000 employees
Founded 2008
đŒ Consulting
đŁ Marketing
đŠ Logistics
Consulting âą Marketing âą Logistics
Lingaro is an end-to-end data services and analytics partner for global brands and enterprises, delivering data strategy, platform engineering, AI/ML (including generative AI), and data governance to unlock business value. It combines domain-focused analytics (supply chain, commercial/RGM, digital commerce, sustainability) with data platforms, visualization, MLOps, and secure cloud (Google Cloud) integrations, plus a creative arm (ALCHEMY) for data-driven brand and commerce experience design.
đ„ 5 minutes ago
đ”đ± Poland â Remote
âł Contract/Temporary
đĄ Mid-level
đ Senior
đ° Data Engineer
đ» Ghost score 11%
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1001 - 5000 employees
Founded 2008
đŒ Consulting
đŁ Marketing
đŠ Logistics
Consulting âą Marketing âą Logistics
Lingaro is an end-to-end data services and analytics partner for global brands and enterprises, delivering data strategy, platform engineering, AI/ML (including generative AI), and data governance to unlock business value. It combines domain-focused analytics (supply chain, commercial/RGM, digital commerce, sustainability) with data platforms, visualization, MLOps, and secure cloud (Google Cloud) integrations, plus a creative arm (ALCHEMY) for data-driven brand and commerce experience design.
âą Collaborate with stakeholders to understand business requirements and translate them into data engineering solutions âą Design and oversee scalable, performant, secure, maintainable data architecture and infrastructure âą Define data models and schemas based on business needs and data characteristics âą Select and integrate databases, data lakes, data warehouses, and big data frameworks âą Create scalable ETL processes, data pipelines, and data integration solutions âą Align data engineering solutions with the organization's long-term data strategy âą Evaluate and recommend data governance, privacy, security, and compliance practices âą Collaborate with data scientists, analysts, and stakeholders to define data requirements and enable analysis and reporting âą Provide technical guidance to data engineering teams and support implementation âą Oversee implementation according to design documents and technical specifications âą Monitor emerging data engineering trends and recommend innovative solutions âą Analyze and optimize system performance, resolving bottlenecks and inefficiencies âą Ensure data quality and integrity through validation and monitoring âą Integrate data engineering solutions with other systems and applications âą Participate in project planning and estimation âą Document data architecture, infrastructure, and design decisions
âą Proven work experience as a Data Engineering Architect or in a similar role âą Strong experience in the Data & Analytics area âą Strong understanding of data modeling, ETL processes, data pipelines, and data governance âą Expertise in designing and implementing scalable and efficient data processing frameworks âą In-depth knowledge of relational databases, NoSQL databases, data lakes, data warehouses, and big data frameworks such as Hadoop and Spark âą Experience selecting and integrating technologies to meet business requirements and long-term data strategy âą Ability to translate stakeholder business needs into data engineering solutions âą Strong analytical and problem-solving skills âą Proficiency in Python, PySpark, and SQL âą Familiarity with AWS, GCP, or Azure and experience designing and implementing cloud data solutions âą Knowledge of data governance principles, data privacy, and security regulations âą Excellent communication and collaboration skills âą Experience leading and mentoring data engineering teams âą Familiarity with agile methodologies and agile development environments âą Continuous learning mindset âą Strong project management skills âą Strong understanding of distributed computing principles, including parallel processing, data partitioning, and fault tolerance âą Bachelor's degree in Computer Science, Information Technology, or a related field âą Master's degree may be preferred
âą Inclusive workplace committed to diversity, equity, and inclusion âą Equal opportunities âą Safe and respectful workplace âą Environment where employees feel valued and empowered to learn and grow
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