Working Student contributing to data engineering projects for AI/ML workflows while gaining hands - on experience with data pipelines and tools.
About the role
- Senior Data Engineer implementing ingestion and transformation pipelines at SONAR in a hybrid role. Collaborating closely with engineering and data science teams in a fast-paced environment.
Responsibilities
- Implementing ingestion pipelines, using Airflow as the orchestration platform, for consuming data from a wide variety of sources (API, SFTP, Cloud Storage Bucket, etc.).
- Implementing transformation pipelines using software engineering best practices and tools (DBT)
- Working closely with Software Engineering and DevOps to maintain reproducible infrastructure and data that serves both API-only customers and in-house SaaS products
- Defining and implementing data ingestion/transformation quality control processes using established frameworks (Pytest, DBT)
- Building pipelines that use multiple technologies and cloud environments (for example, an Airflow pipeline pulling a file from an S3 bucket and loading the data into BigQuery)
- Create and ensure data automation stability with associated monitoring tools.
- Review existing and proposed infrastructure for architectural enhancements that follow both software engineering and data analytics best practices.
- Working closely with Data Science and facilitating advanced data analysis (like Machine Learning)
Requirements
- Strong working knowledge of Apache Airflow
- Experience supporting a SaaS or DaaS product, bonus points if you were creating new data products/features
- Strong in Linux environments and experience in scripting languages Python
- Expert Strong understanding of software best practices and associated tools.
- Experience in any major RDBMS (MySQL, Postgres, SQL Server, etc.).
- Strong SQL Skills, bonus points for having used both T-SQL and Standard SQL
- Experience with NoSQL (Elasticsearch, MongoDB, etc.)
- Multi-cloud and/or hybrid-cloud experience
- Strong interpersonal skills
- Comfortable working directly with data providers, including non-technical individuals
- Experience with the following (or transitioning from equivalent platform services): Cloud Storage, Cloud Pubsub, BigQuery, Apache Airflow, dbt, DataFlow
- Bonus knowledge/experience: Experience implementing cloud architecture changes
- Working knowledge of how to build and maintain APIs using Python/FastAPI
- Transforming similar data from disparate sources to create canonical data structures
- Surfacing data to BI platforms such as Looker Studio
- Data Migration experience, especially from one cloud platform to another
- Certification: Professional Google Cloud Certified Data Engineer
Benefits
- An excellent work environment, flat hierarchies, and short decision paths
- A generous benefits package including 100% employer-paid health, dental, vision and Life insurance, STD, LTD
- Stock options
- Appealing 401k matching plan
- Personal Development Credit (Can be used toward Student loans or relevant PD Courses)
- Annual life achievement bonus for having a baby, buying a house, or getting married (max one per year)
- No set days off
- Vacation policy (our team takes time off as needed with supervisor approval)
- Up to $50 for Gym or Virtual Gym membership.
- Up to $20 for AI subscription (ChatGPT, Grok, etc.)
Job title
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