AWS Data Engineer

About this role

Title: AWS Data Engineer

Location: Seattle, WA

Role Summary

Seeking an AWS Data Engineer to design, build, and optimize large-scale data pipelines and analytics solutions on AWS. This role is responsible for the end-to-end data lifecycle, including data ingestion, transformation, storage, and delivery for analytics, machine learning, and operational systems.

Key Responsibilities

• Design, build, and optimize ETL/ELT workflows to ingest data from multiple sources (S3, Redshift, Lake Formation, Glue, Lambda).
• Implement data cleansing, enrichment, and standardization processes.
• Develop and automate batch and real-time streaming data pipelines using Kinesis, MSK, Lambda, Glue, EMR, and Step Functions.
• Ensure pipelines are optimized for scalability, performance, and fault tolerance.
• Optimize SQL queries, data models, and pipeline performance.
• Design and implement data architecture across data lakes, data warehouses, and lakehouses.
• Optimize data storage strategies including partitioning, indexing, and schema design.
• Integrate data from diverse sources such as databases, APIs, IoT, and third-party systems.
• Collaborate with Data Scientists, Analysts, and BI developers to deliver structured data.
• Document data assets and processes for discoverability.
• Train internal staff to maintain infrastructure and pipelines.

Required Technical Skills

• Strong experience with AWS services: S3, Redshift, Lake Formation, Glue, Lambda, Kinesis, MSK, EMR, Step Functions.
• Proficiency in SQL, Python, or Scala for data transformation and processing.
• Hands-on experience with Databricks on AWS.
• Working knowledge of DevOps and CI/CD practices.
• Experience designing data pipelines for batch and streaming architectures.
• Experience with utility industry data (meter data, customer data, grid/asset data, work management, outage data).
• Familiarity with IEC CIM standards and utility integration frameworks.

Preferred / Nice-to-Have Skills

• Experience with ...