Data Operations & Intelligence Engineer

Description and Requirements Join Lenovo's Solutions & Services Group (SSG ) as a Data Engineering & Analytics Specialist and help shape the future of APOS HQ's business data ecosystem. Reporting directly to the APOS HQ Sr. Data Manager, you will play a key role in discovering, structuring, and improving business-critical data that drives strategic decision-making across the organization. This is a highly visible opportunity where you'll gain meaningful ownership from day one, tackle complex and evolving business challenges, collaborate with cross-functional stakeholders, and contribute to high-impact initiatives. You'll also have access to modern AI-powered tools that accelerate coding, research, and data exploration, while building a strong foundation for future growth in data engineering, analytics, data architecture, or data science. This role is ideal for someone who is naturally curious, technically strong, analytical, and energized by solving ambiguous problems and transforming complex data into actionable business value. What You Will Do: Explore, analyze, and validate data from Hadoop-based and other upstream data environments to uncover insights and support business decision-making. Design, develop, and continuously improve ETL processes that power the APOS curated business data model and ensure scalable data delivery. Investigate complex data issues, source system logic, anomalies, gaps, and inconsistencies, driving root-cause analysis and resolution across teams. Transform and integrate data from multiple sources, including incomplete or inconsistent datasets, into reliable and business-ready solutions. Optimize SQL queries, ETL logic, and data transformations to improve performance, scalability, and efficiency across large data volumes. Define, monitor, and enhance data quality, coverage, reliability, and governance measures to ensure trusted business data assets. Support strategic data initiatives, including entity linkage, account-contact relationships, business rule refinement, success measurement frameworks, and feedback loop design. Partner closely with IT teams, data owners, and business stakeholders to document data logic, identify risks, prioritize backlog improvements, and drive the evolution of a business-focused data ecosystem. What You Will Bring: Strong SQL skills with the ability to extract, transform, analyze, and optimize data across complex datasets and business environments. Experience in data engineering, analytics engineering, data operations, business intelligence, or a similar data-focused role. Comfortable working independently in exploratory environments where requirements may evolve and solutions need to be built from the ground up. Strong communication and stakeholder management skills, with the ability to collaborate directly with data owners, technical teams, and business partners. Hands-on experience with Hadoop-based data ecosystems and distributed query technologies such as Spark SQL, Trino, Hive SQL, or similar platforms is highly preferred. Experience designing, building, supporting, and optimizing ETL pipelines, including query performance tuning and large-scale data processing. Knowledge of data quality frameworks, validation methodologies, and best practices for ensuring reliable and trusted data assets. Additional experience with Python, Metabase, statistical analysis, Power BI, Qlik, Tableau, or Lenovo internal platforms (Flex, LUDP, Magellan) would be considered a strong advantage. What We Offer: Opportunities for career development & growth Performance based rewards Hybrid working model (homeoffice/office) Up to 3 paid Personal Days annually Additional vacation days 100% sick leave compensation up to 2 months per year A broad selection of soft / hard skills trainings and individual mentoring Employer contribution to the Third Pillar Pension System Life & life events insurance, fully covered by company  We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.