Senior Data Engineer
New
C
CeligoIPaaS
Location: USFull-TimeSenior
Salary130,000 - 170,000 USD per year
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Job Details
- Experience
- 5+ years of hands-on experience in data engineering, specifically building production-grade pipelines and distributed computing frameworks. 3+ years working directly with Snowflake in a production capacity.
- Required Skills
- PythonSQLSnowflakeAirflowCI/CDData modelingdbt
Requirements
- 5+ years of hands-on experience in data engineering, specifically building production-grade pipelines and distributed computing frameworks.
- 3+ years working directly with Snowflake in a production capacity.
- Advanced proficiency in SQL and at least one programming language (Python preferred).
- Deep expertise in Snowflake architecture, including virtual warehouse configuration, clustering, data sharing, role-based access control, and cost governance.
- Strong command of modern ELT tooling such as dbt, Fivetran, Airflow, or Prefect in a Snowflake-native environment.
- Demonstrated experience in architecting or contributing to at least one full data warehouse migration or rebuild on Snowflake.
- Experience with version-controlled, CI/CD-driven data pipeline development (e.g., dbt + GitHub Actions or equivalent).
- Familiarity with data governance, security, and compliance considerations in a cloud data warehouse context.
- Hands-on experience integrating AI/ML tools into the development cycle.
- Degree in Computer Science, Engineering, or a related technical field.
Responsibilities
- Design, build, and maintain scalable ELT/ETL pipelines and data infrastructure using Snowflake and modern tooling.
- Architect and implement data models — including dimensional, data vault, and medallion/lakehouse patterns — to support analytics, BI, and ML use cases.
- Collaborate with Analytics, Product, and Engineering teams to translate business requirements into reliable, well-documented data solutions.
- Establish and enforce data quality standards, automated validations, and observability frameworks to ensure high reliability across all pipelines.
- Contribute to data governance practices, including documentation, data lineage, access control, and compliance standards.
- Monitor and optimize pipeline performance, compute cost efficiency, and data freshness across the warehouse.
- Evaluate and implement emerging Snowflake features and data tooling to improve engineering velocity and reduce costs.
- Leverage AI-assisted development tools (e.g., Claude Code, GitHub Copilot, Cursor, or equivalent) to accelerate pipeline development, code review, and documentation.
- Participate in code reviews, architectural discussions, and cross-functional technical planning sessions.
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