Senior Cloud Data Engineer
Location: New York, NY (Hybrid)
Experience Level: 5–8 Years
Job Summary
We are seeking a Senior Cloud Data Engineer to design, build, and optimize scalable data infrastructure in a cloud environment. You will be responsible for the end-to-end data lifecycle, from ingestion to production-grade pipelines that support advanced analytics and machine learning.
Key Responsibilities
- Pipeline Architecture: Architect and maintain robust ETL/ELT pipelines using tools like dbt, Airflow, or Prefect.
- Cloud Infrastructure: Manage and optimize data storage and compute on major platforms like AWS, Azure, or GCP.
- Data Modeling: Design complex schemas (Star, Snowflake, or Data Vault) for high-performance data warehousing in Snowflake, BigQuery, or Databricks.
- Optimization: Monitor and tune query performance and data processing workflows to ensure cost-efficiency and scalability.
- Collaboration: Partner with Data Scientists and Product Managers to translate business requirements into technical data products.
- Governance & Security: Implement best practices for data quality, security (RBAC), and compliance frameworks.
- Dataquest +5
Required Qualifications
- Experience: 5–8 years of professional experience in data or cloud engineering.
- Programming: Advanced proficiency in Python (Pandas, PySpark) and SQL (window functions, query optimization).
- Distributed Systems: Hands-on experience with big data technologies such as Apache Spark, Kafka, or Flink.
- DevOps: Familiarity with CI/CD pipelines, Git-based workflows, and Infrastructure-as-Code (Terraform/CDK).
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
- Dataquest +5
Salary & Benefits
- Base Salary: $175,000 – $250,000 (varies by industry and specific skill set).
- Additional Comp: Bonus eligible 20% target
- Standard Benefits: Medical/Dental/Vision, 401(k) matching, and commuter benefits for NYC-based employees.
