Description and Requirements
This role is open for the Edinburgh, Scotland location only. Candidates must be based there, as the position requires working from the office at least three days per week (3:2 hybrid policy).
Lenovo is seeking a talented and motivated Sr. Data Engineer/Scientist to join our growing team. This role is critical to the success of our machine learning initiatives, focusing on the creation, quality control, and governance of the datasets that power our models. You will bridge the gap between raw data and model readiness, working closely with model developers to understand their needs and deliver high-quality, reliable data. This is a hands-on role requiring strong technical skills in data engineering, data analysis, and machine learning fundamentals. If you are passionate about making Smarter Technology For All, come help us realize our Hybrid AI vision!
Responsibilities:
1. Data Creation & Annotation: Design, build, and implement processes for creating task-specific training datasets. This may include data labeling, annotation, and data augmentation techniques.
2. Data Pipeline Development: Leverage tools and technologies to accelerate dataset creation and improvement. This includes scripting, automation, and potentially working with data labeling platforms.
3. Data Quality & Evaluation: Perform thorough data analysis to assess data quality, identify anomalies, and ensure data integrity. Utilize machine learning tools and techniques to evaluate dataset performance and identify areas for improvement.
4. Big Data Technologies: Utilize database systems (SQL and NoSQL) and big data tools Spark, Hadoop, cloud-based data warehouses like Snowflake/Redshift/BigQuery) to process, transform, and store large datasets.
5. Data Governance & Lineage: Implement and maintain data governance best practices, including data source tracking, data lineage documentation, and license management. Ensure compliance with data privacy regulations.
6. Collaboration with Model Developers: Work closely with machine learning engineers and data scientists to understand their data requirements, provide clean and well-documented datasets, and iterate on data solutions based on model performance feedback.
7. Documentation: Create and maintain clear and concise documentation for data pipelines, data quality checks, and data governance procedures.
8. Stay Current: Keep up-to-date with the latest advancements in data engineering, machine learning, and data governance.
Qualifications:
9. Education: Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Mathematics, or a related field.
10. Experience: 15+ years of experience in a data engineering or data science role.
11. Programming Skills: Mastery in Python and SQL. Experience with other languages Java, Scala) is a plus.
12. Database Skills: Strong experience with relational databases PostgreSQL, MySQL) and NoSQL databases MongoDB, Cassandra).
13. Big Data Tools: Experience with big data technologies such as Spark, Hadoop, or cloud-based data warehousing solutions (Snowflake, Redshift, BigQuery).
14. Data Manipulation: Proficiency in data manipulation and cleaning techniques using tools like Pandas, NumPy, and other data processing libraries.
15. ML Fundamentals: Solid understanding of machine learning concepts and techniques, including data preprocessing, feature engineering, and model evaluation.
16. Data Governance: Understanding of data governance principles and practices, including data lineage, data quality, and data security.
17. Communication Skills: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
18. Problem Solving: Strong analytical and problem-solving skills.
Bonus Points:
19. Experience with data labeling platforms Labelbox, Scale AI, Amazon SageMaker Ground Truth).
20. Experience with MLOps practices and tools Kubeflow, MLflow).
21. Experience with cloud platforms AWS, Azure, GCP).
22. Experience with data visualization tools Tableau, Power BI).
23. Experience with building and maintaining data pipelines using orchestration tools Airflow, Prefect)
What we offer:
24. Holiday purchase
25. Private medical
26. Income protection
27. Attractive pension scheme
28. Positive work life balance
29. Learning and development
30. Life insurance
31. Lenovo and Motorola products discounts
32. Lifestyle discounts
33. Cycle to work
34. MyGymDiscounts
35. Mortgage advice and support
36. Referral bonus
37. Electric car salary sacrifice scheme
38. Free onsite parking