Cloud Data Engineer

CloudAI Technologies; Washington (District of Columbia); On-site; USD 150,000 - 190,000; Full time

Job summary

CloudAI Technologies in Washington, DC seeks an experienced Senior Data Engineer to design, build and operate scalable production data pipelines and cloud data platforms. You will implement ELT, ensure data quality and governance, and migrate from legacy ETL tooling across multi‑cloud environments including Databricks, Snowflake, Azure and AWS.

Applicants must reside in the United States and be authorized to work here. The role offers exposure to public sector and higher‑ed clients as a plus.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
• Eight (8) years of professional data engineering experience building and operating production data pipelines.
• Experience delivering a cloud data platform on Databricks or Snowflake through full lifecycle to production.
• Experience working across more than one cloud, including Databricks on both Azure and AWS.
• Experience with ELT at scale, including incremental processing and tuning for cost and performance.
• Experience implementing data quality, governance, and lineage controls on a production platform.
• Experience migrating from legacy ETL tooling or an on-premises warehouse preferred.
• Experience with public sector or higher education clients preferred, not required.
• Must reside in the United States and be authorized to work in the United States.

Skills

Data Engineering

Databricks

Snowflake

Azure

AWS

ELT at scale

Data Governance

Data Quality

ETL Migration

Public Sector

Education

Bachelor's degree

Tools

Databricks Platform

Snowflake

Azure

AWS

Job description

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
• Eight (8) years of professional data engineering experience building and operating production data pipelines.
• Demonstrated experience delivering a cloud data platform on Databricks or Snowflake through full lifecycle to production.
• Demonstrated experience working across more than one cloud, including Databricks on both Azure and AWS.
• Experience with ELT at scale, including incremental processing and the cost and performance tuning that goes with it.
• Experience implementing data quality, governance, and lineage controls on a production platform.
• Experience migrating from legacy ETL tooling or an on-premises warehouse preferred.
• Experience with public sector, SLED (state, local, and education), or higher-education clients preferred, not required.
• Must physically reside in the United States and be authorized to work in the United States. U.S. citizenship or permanent residency is not required.

Certifications

• No certification required for this role.
• Platform certification preferred (e.g., Databricks Certified Data Engineer Professional, SnowPro Advanced, Microsoft Certified: Azure Data Engineer Associate).