Senior Data Engineer - AI Platform

Description and Requirements

At Lenovo, we Never Stand Still. Every day, every employee at Lenovo is focused on moving forward, rejecting traditional limits, and always seeking a better way.

Do you have a passion for data and building pipelines that power cutting edge AI? Are you a results-oriented engineer who thrives in a collaborative environment?

If so, we want to hear from you! We’re looking for a Senior Data Engineer to work with the AI platform team within our Cloud and Software (CSW) Group at Lenovo.

About the role

In this role you will work directly with locally & globally distributed teams responsible for defining, designing and building robust data pipelines and data serving platforms in a cloud-based SaaS environment.

You’ll be part of a highly dynamic software development team working on initiatives with a goal to transform and enhance the overall business value of our products and platforms.

You will be responsible for using distributed data processing frameworks to ingest, extract, transform, store, serve and build data sets that could be used by AI applications, Data Scientists and ML will apply your knowledge of algorithms, pipelines, cloud expertise, AI & ML, data processing, supporting tools and technologies to develop new data solutions.

As a Senior Data Engineer on the team, you will play a key role in improving existing data models, pipelines and maintaining them for a worldwide customer base.

This is a great opportunity if you are :

• passionate about data
• have a strong sense of responsibility and ownership
• resourceful in face of ambiguity and thrive on change
• an independent thinker who can solve complex problems
• an excellent collaborator and with solid communication skills, demonstrated by successful cross team collaboration

Responsibilities :

• In this role, you will work on the user, device and services data ingestion and storage platform that is an integral part of the AI ecosystem
• The data you shape will be used to power AI capabilities of the core platform that enables various cloud solutions of the company.
• As a Senior Data Engineer, you will be responsible for developing new data pipelines for data ingestion and transformation, building / updating capabilities of the existing data pipelines including real-time streaming and batch processing.
• You will take end to end ownership of implementing solutions to the identified issues with the focus on quality, stability, security and customer satisfaction.
• You'll collaborate with a multidisciplinary, globally distributed team of professionals that can include Data Scientists, Machine Learning Engineers, Business Analysts, Project and Product Management
• Designing, building, implementing, and documenting data models
• Working with business partners to understand business and product objectives, identify the data needed to support them, while influencing the decisions
• Optimizing data transformation pipelines to improve latency or reduce computational time, cost.
• Proactively contribute to the development of the data engineering team by mentoring junior engineers

Minimum Qualifications :

• Bachelor's degree in computer science, Information Systems, Engineering, Math or related technical field.
• 8+ years of relevant software development experience
• 5+ years of experience :
• Developing and maintaining data processing pipelines using Spark, Hadoop, Hive.
• Working with programming languages such as Java and Python
• Data Engineering, and / or building scalable streaming and / or batch data pipelines
• Data Engineering tooling : collection, cleaning, transformation, ingestion, storage, publishing
• Experience mentoring junior engineers and help grow their technical skills

Preferred Qualifications :

• Advanced SQL skills (such as window functions, defining UDFs)
• Experience working with relational as well as NoSQL databases and streaming platforms such as Kafka
• Familiarity with version control systems, CI / CD practices, testing
• Experience with data discovery, lineage, data governance, data orchestration, data quality metrics measurement is plus
• Experience working with machine learning engineers, data scientists, and ML applications is plus
• Experience working with data pipelines for LLM applications is plus
• Experience with tools like Docker and platforms such as Kubernetes (K8S).

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