Quick Summary
Overview
We are building the next generation of our enterprise data platform and are seeking a Cloud Data Engineer to architect, develop, and optimize large-scale, cloud-native data warehousing and ETL pipelines on AWS.
Technical Tools
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We are building the next generation of our enterprise data platform and are seeking a Cloud Data Engineer to architect, develop, and optimize large-scale, cloud-native data warehousing and ETL pipelines on AWS.
You will be responsible for designing our data warehouses, implementing scalable AWS-based ingestion and transformation pipelines, and enabling high-quality analytics and BI across the organization.
This role is ideal for someone with deep hands-on engineering expertise in cloud data ecosystems, data modeling, analytics enablement, and modern ETL patterns
ESSENTIAL DUTIES AND RESPONSIBILITIES
Design and implement AWS-native ETL/ELT pipelines using services such as:
AWS Glue
AWS Lambda
Amazon MWAA / Apache Airflow
Step Functions
S# / Lake Formation
Architect and maintain data warehouses using Amazon Redshift (or Snowflake/Databricks on AWS).
Build robust data ingestion patterns including incremental loads, partitioning strategies, and schema evolution handling.
Ensure pipelines are secure, observable, cost‑efficient, and reliable in production environments.
REQUIRED SKILLS AND ABILITIES
Strong understanding of data warehousing concepts and best practices
Expertise in SQL and query optimization for large-scale datasets
Proficiency in cloud data platforms (AWS preferred) and associated services (Glue, Lambda, Airflow, S3, etc.)
Strong programming skills (e.g., Python, C#, or similar) for ETL development and automation
Experience designing and implementing scalable ETL/ELT pipelines
Knowledge of modern data formats (Parquet, JSON, ORC) and file-based processing
Experience with data modeling (star/snowflake schemas, fact/dimension design)
Familiarity with data governance, lineage, and security in cloud environments
Experience integrating AI/LLM tools into engineering workflows is a plus
Strong written and verbal communication skills
Ability to manage multiple priorities and meet deadlines in a fast-paced environment
KNOWLEDGE, EXPERIENCE, AND/OR EDUCATION REQUIREMENTS
Bachelor’s degree preferred but not required
In lieu of a degree, equivalent experience in data engineering, computer science, or related field
2-4 years of experience in data engineering or data warehousing
Hands-on experience with cloud data platforms (AWS strongly preferred)
Experience building and maintaining large-scale data pipelines and warehouses
Experience working with BI tools such as Tableau, Power BI, Quick Sight or similar
Experience with applied AI in data workflows is a plus
Disclaimer: This job description is not intended to be an exhaustive list of all duties, responsibilities, or qualifications associated with the job. Management reserves the right to modify or reassign job duties as business needs evolve.
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Location & Eligibility
Where is the job
Worldwide
Fully remote, anywhere in the world
Who can apply
Same as job location
Listing Details
- Posted
- April 15, 2026
- First seen
- May 6, 2026
- Last seen
- May 8, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 20%
- Scored at
- May 6, 2026
Signal breakdown
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External application · ~5 min on empyrean's site
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