- Minimum 3-5 years' experience with | Python.
- Minimum 2+ years' experience with SQL.
- Minimum 3-5 years' experience with Data modeling.
- Minimum 5 years' experience with Big data pipelines.
- Minimum 3-5 years' experience with Cloud experience.
- Collaborate with data consumers and stakeholders to understand their data needs.
- Identify and analyze multi-structured data from a variety of sources to select the most effective and accurate data which fulfills the analytics requirements.
- Design data models, architect dataflows, and create technical requirements to deliver solutions.
- Build and maintain automated data pipelines to source and transform data into clean, enriched, and optimized polyglot data models which can evolve with changing needs.
- Use modern data engineering practices and frameworks to create scalable big data solutions for analytics and machine learning, while ensuring data quality.
- Write and maintain technical documentation for the data models and analytics solutions.
- Assist Users with data access tools and documentation to unlock the value of the analytics data.
- Provide stewardship in the creation, collection, maintenance, and documentation of metadata.
- Handle confidential information responsibly and correctly apply security and privacy policies.
- 5+ years working as a data engineer or equivalent on large enterprise systems.
- Critical thinker and problem solver who brings a creative and open mindset to each situation.
- A proven track record building and optimizing big data pipelines for analytic solutions.
- Data analysis skills to identify, select and prepare quality data for analytics use cases.
- Experience building enterprise scale data pipelines on Cloud Data Platforms using Spark and Databricks for ETL/ELT, data products, or Machine Learning; Azure preferred.
- API and application development experience for data access and analytics solutions.
- Strong Python skills for data processing combined with a pythonic mindset. Proficient SQL.
- Working knowledge handling logs or event streaming data sources.
- Working knowledge of DevOps and DataOps including feature planning, version control, multi-environment, CI/CD, data-modeling, automation, governance, and continuous improvement.
- Video game domain knowledge is important - as an experienced Player or industry veteran.
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Data Scientist - Redmond, United States - netPolarity
Description
I would like to set up a time to discuss the potential opportunity below:
Role: Data Scientist
Location: Redmond, WA or Remote
Duration: 1 months
Top 3 Hard Skills Required + Years of Experience
Responsibilities:
Qualifications: