Tech Lead
hace 2 semanas
Job Description
Analyzing, designing, developing and managing the infrastructure and the data that feeds Data Science models. The Technical Lead is expected to contribute to the design of any solutions that complement the ML components. In addition, this person should be able to lead and guide a team of engineers to provide the best solutions to get the research into production deliverables.
**Responsibilities**:
- Managing the lifecycle (from data collection to archive) of ML/DL datasets ensuring their usability for Nielsen’s Data Scientists.
- Design, build and integrate data from various sources.
- Working closely with data scientists and a variety of end-users (across different cultures) to ensure technical compatibility and user satisfaction.
- Design ETL pipelines with scripted components.
- Optimize data workflows, choosing the most cost-efficient approach.
- Automate the management of recurrent task in the pipeline.
- Perform feasibility studies/analysis with a critical point of view.-
- Work on many different software challenges always ensuring a combination of simplicity and maintainability within the code.
- Contribute to architectural designs of large complexity and size, potentially involving several distinct software components.
- Work as a member of a team, encouraging team building, motivation and cultivate effective team relations.
**Role Requirements**
E=essential, P=preferred.
E - Bachelor's degree in computer engineering.
P - Master’s degree in data engineering or related.
E - Demonstrated experience and knowledge in Big Data and NoSQL databases.
E - Demonstrated experience and knowledge in Object-Oriented Programming.
E - Demonstrated experience and knowledge in distributed systems.
E - Proficient in programming languages: Python.
E - Experience designing and implementing data warehouses.
E - Experience developing ETL pipelines.
E - Experience working in cloud environments (preferably Azure)
E - Experience working with distributed storage systems in the cloud (Azure, GCP or AWS).
P - Experience managing deep learning datasets.
E - Experience with MLOps pipelines.
P - Experience working with Spark.
P - Experience implementing CICD pipelines for automation.
E - Experience in the use of collaborative developing tools such as Git, Confluence, Jira, etc.
E - Problem-solving capabilities.
E - Strong ability to analyze and synthesize. (Good analytical and logical thinking capability)
E - Proactive attitude, resolutive, used to work in a team and manage deadlines.
E - Ability to learn quickly.
E - Agile methodologies development (SCRUM/KANBAN).
E - Minimal work experience of 8-10 years with evidence.
E - Ability to keep fluid communication written and oral in English, both written and spoken.
Additional Information
All your information will be kept confidential according to EEO guidelines.
**About NielsenIQ**
NielsenIQ is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class.
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