Cloud Data Engineer

Empyrean Benefit Solutions • Houston, TX

1d • Remote

About The Position

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

Requirements

• 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
• Strong written and verbal communication skills
• Ability to manage multiple priorities and meet deadlines in a fast-paced environment
• 5–8 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

Nice To Haves

• Experience integrating AI/LLM tools into engineering workflows is a plus
• Experience with applied AI in data workflows is a plus

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level