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Senior Data Engineer
PayscaleUnited Statesfull_timeVerifiedPosted 1 Oct 2024
💰 $201,400/yr($134,200/yr – $201,400/yr)
About the role
Are you passionate about empowering teams to make data-driven decisions? Do you find yourself excited about the possibilities that more data can unlock? Payscale is seeking a seasoned engineer to join our Data Engineering Team. Our team focuses on enabling fast, accurate, and reliable access to data by building robust data pipelines, managing our data warehouse, and supporting the productization of our data. Responsibilities:
- Manage the data warehouse.
- Maintain and build new data pipelines.
- Partner with our platform, architectural and product development teams to design and influence modern architectural solutions.
- Collaborate with various teams (Data Science, Data Analytics, Application Engineering, Sales, Customer-Facing Teams) to meet their data access needs.
- Evangelize best practices for data utilization, data modeling, cost efficiency, and query optimization among stakeholders, junior engineers, and warehouse consumers.
- Research and advise on modern data engineering techniques.
- Build and support tools and services for data management, monitoring, and productization.
- Recommend and implement tools and technologies to support PayScale's evolving data needs.
- Oversee data hygiene and conduct cost analysis.
- Data Warehousing and Reporting: Snowflake, Spark, Tableau
- ETL and Pipelining: Fivetran, Python, TeamCity, AWS Lambda
- Additional Technologies: C#, Docker, Kubernetes, Azure, AWS, Redis, DynamoDB, SQL Server, MongoDB, Elasticsearch, Postgres, Octopus Deploy
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 5+ years of experience in data warehousing and data engineering.
- Hands-on experience with Snowflake data warehouse platform for data storage, retrieval, and analysis.
- Experience in optimizing data workflows, ensuring data quality, and managing data transformations within Snowflake or similar platforms.
- Expert level programming skills in Python, SQL
- Experience in building AI/ML retraining pipelines
- Experience in designing and deploying APIs in cloud environments (e.g., AWS, Azure, GCP) while considering scalability and elasticity requirements.
- Proficiency in machine learning development, including experience with training, fine-tuning, and validating ML models using frameworks like TensorFlow, PyTorch, or similar.
- In-depth knowledge of AI/ML model evaluation, optimization, and deployment strategies.
- Strong understanding of vector databases and their application in AI/ML model storage and retrieval.
- Experience in utilizing Large Language Models (LLMs) such as GPT (Generative Pre-trained Transformer), BERT (Bidirectional Encoder Representations from Transformers), LLaMa (Meta AI), or similar models in r
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