Data Engineer
Sennos
About Sennos Sennos is rapidly emerging as the global leader in AI-driven sensing, analytics, and control for the Fluid, Fermentation, and Bio-manufacturing industries. With a revolutionary integration of hardware, software, and real-time multi-parametric data, we have quietly built the world's most advanced sensing system and largest AI-powered fermentation data warehouse. By owning the entire stack-from sensing hardware to data infrastructure-we have delivered a breakthrough solution that reveals complex biological and chemical interactions, predicts precision outcomes, and enables next-generation production control. Sennos is a rapidly growing start-up looking for someone who can quickly adapt to a changing environment and who has the desire to grow with us! Position Summary The Data Engineer sits within the Data & Analytics organization and supports the development and ongoing improvement of Sennos' modern data platform. This role focuses on building and maintaining data pipelines, implementing transformations, and contributing to a reliable Snowflake-based warehouse that powers analytics, reporting, machine learning, and product capabilities. Working closely with senior data engineering leadership, data architecture, analytics engineering, and product teams, this role combines hands-on technical execution with growing exposure to data modeling, quality enforcement, and scalable platform development. Responsibilities
Applicants must be permanently authorized to work for ANY employer in the United States. We are unable to sponsor or take over sponsorship of an employment visa at this time. Recruitment Agency Notice: We do not accept unsolicited candidate submissions. We only work with recruitment agencies that have a signed agreement with our HR team. Unsolicited resumes will not incur any fee obligation.
- Build and maintain ETL/ELT pipelines using SQL and Python under the guidance of senior data engineering leadership
- Develop and maintain transformations using dbt or similar tools within a Snowflake-based warehouse
- Create and optimize datasets and views to support analytics, reporting, machine learning, and product feature development
- Manage ad hoc data requests with accuracy and efficiency while maintaining data integrity and consistency
- Implement and maintain data quality checks, validation rules, and testing processes to ensure reliability and trust in warehouse data
- Support the enforcement of data contracts between source systems and the warehouse
- Assist in reverse ETL workflows to operationalize warehouse data into downstream systems
- Contribute to ML data preparation and feature pipeline workflows
- Collaborate closely with Data Architecture, Analytics Engineering, Product, and Software Engineering teams
- Contribute to documentation, governance practices, and continuous improvement of data engineering standards
- Bachelor's degree in Computer Science, Data Science, Engineering, or related field (or equivalent years of professional experience)
- 2-4 years of experience in data engineering or a related data-focused role
- Experience working with ETL/ELT processes and structured warehouse data
- Exposure to cloud-based data platforms (AWS preferred)
- Strong SQL skills (joins, window functions, and query optimization fundamentals)
- Proficiency in Python for data processing, scripting, or automation
- Familiarity with version control systems (e.g., Git)
- Strong attention to detail and commitment to data accuracy
- Ability to troubleshoot and debug data workflows effectively
- Strong written and verbal communication skills
- Ability to collaborate across technical and non-technical teams
- Experience working with Snowflake or similar cloud data warehouses
- Exposure to dbt or similar transformation frameworks
- Introductory experience with dimensional modeling concepts
- Experience implementing data quality tests or validation frameworks
- Exposure to data contracts or schema management practices
- Familiarity with reverse ETL concepts
- Passing experience with workflow orchestration tools (e.g., Airflow, Dagster, or similar)
- Familiarity with CI/CD practices for data workflows
- Experience using AI-assisted tools to support debugging, pipeline development, or data engineering workflows
- Exposure to BI tools (e.g., Power BI, Tableau, Looker)
- Collaborative and supportive, with strong mentorship from senior data engineering leadership
- Focused on building durable foundations while moving quickly to meet evolving needs
- Values curiosity, precision, and continuous skill development
- Ability to sit for extended periods while working at a computer
- Office setting with remote/hybrid flexibility
- Minimal travel required (occasional team meetings or company events)
Applicants must be permanently authorized to work for ANY employer in the United States. We are unable to sponsor or take over sponsorship of an employment visa at this time. Recruitment Agency Notice: We do not accept unsolicited candidate submissions. We only work with recruitment agencies that have a signed agreement with our HR team. Unsolicited resumes will not incur any fee obligation.
Vacancy posted 4 days ago
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