Why Work at Lenovo
Description and Requirements
Lead Data Engineer
As a Lead Data Engineer, you will indeed play a crucial role in developing and deploying DataOps and Data Engineering to build data products. Your responsibilities will include working directly with both locally and globally distributed teams to define, design, and build robust data pipelines and data serving platforms in a cloud-based SaaS environment. You will be part of a dynamic software development team focused on transforming and enhancing the overall business value of our products and platforms1.
In this role, you will use distributed data processing frameworks to ingest, extract, transform, store, serve, and build data sets that can be used by AI applications, Data Scientists, and ML engineers. You will apply your knowledge of algorithms, pipelines, cloud expertise, AI & ML, data processing, and supporting tools and technologies to develop new data solutions. Additionally, you will be responsible for improving existing data models and pipelines and maintaining them for a worldwide customer base
Responsibilities
- Scope, design, and build scalable, resilient Data Lakehouse components
- Lead architecture sessions and reviews with peers and leadership
- Exemplary ability to design and develop, perform experiments.
- Accountable for the quality, usability, and performance of the solutions
- Spearhead new software evaluations and innovate with new tooling
- Determine and support resource requirements, evaluate operational processes, measure outcomes to ensure desired results, and demonstrate adaptability and sponsoring continuous learning
- Collaborate with customers, team members, and other engineering teams to solve our toughest problems
- Be a role model and mentor, helping to coach and strengthen the technical expertise and know-how of our engineering community.
- Consistently share best practices and improve processes within and across teams Collaborating with a multidisciplinary, globally distributed team of professionals that can include Data Scientists, Data Engineers, Business Analysts, Project and Product Management
- Ensure data security, compliance, and governance standards are met.
- Identify and resolve data bottlenecks and performance issues.
Minimum Qualifications
- Bachelors degree in Computer Science, Information Systems, Engineering, Math or related technical field.
- 5+ years of experience in designing, implementing, and managing data pipelines and workflows to ensure reliable data integration and processing.
- 5 + years of experience in developing, testing, and maintaining scalable and robust data architectures, data models, and ETL processes.
- 5+ years of experience with open-source compute engines (Apache Spark, Apache Flink, Trino/Presto, or equivalent)
- 3+ years of experience in managing data storage solutions, including databases, data lakes, and data warehouses.
- 3+ years of experience with cloud computing (AWS, Microsoft Azure, Google Cloud, Hybrid Cloud, or equivalent)
- 3+ years of experience with observability tools like Datadog, ELK stack (Elasticsearch, Logstash, Kibana), and similar.
- 2+ years of experience developing new and enhancing existing open-source based Data Lakehouse platform components
- 2+ years of experience with open-source table formats (Apache Iceberg, Delta, Hudi or equivalent)
- 2+ years of expertise in developing distributed systems that are scalable, resilient, and highly available.
- 2+ years of expertise in container technology like Docker and Kubernetes platform development
Preferred Qualifications
- Masters degree in Computer Science, Information Systems, Engineering, Math or related technical field.
- Experience mentoring junior engineers and help grow their technical skills
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