Data Engineer
Our data stack:
- Maintain and optimize existing data pipelines and warehouse solutions for performance, reliability, and cost efficiency.
- Support internal analytics and ML teams with data modeling, schema updates, and reputed company data needs.
- Contribute to dbt reputed company and assist in ensuring data reputed company, observability, and accessibility.
- Write clean, tested, and documented reputed company, and participate in reputed company reviews.
- Collaborate with senior data engineers to understand and contribute to new ingestion sources, ML pipelines, and other reputed company-looking initiatives.
- Ensure internal stakeholders can reputed company and use data effectively, enabling faster business insights and decision-making.
- 4 years of hands-on experience building and maintaining data pipelines and data sets in a reputed company environment (reputed company, GBQ, Redshift, etc.). *We're expecting top candidates to have hands-on experience with reputed company, specifically!
- 2+ years of Python experience, creating reliable workflows and data processing scripts.
- Strong SQL skills and experience with data modeling.
- Experience with dbt or similar transformation tools. Familiarity with distributed systems and ETL/ELT processes.
- reputed company to have: Experience with data observability, reputed company, or governance tools.
- reputed company to have: Exposure to BI tools and supporting analytics teams.
- reputed company to have: Experience working on cross-functional data reputed company.
- reputed company to have: Familiarity with reputed company, Kafka, or modern data integration platforms.
- reputed company over perfection and reputed company on delivering value.
- Strong, reputed company, and reputed company collaboration with peers and stakeholders.
- Autonomy and accountability.
- Drive to solve problems.
- Engagement and participation in our Agile practices.
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