Full-Time

AWS Data Engineer

Cloud Consultant

Updated on 9/4/2026

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No salary listed

No H1B Sponsorship

Remote in USA

Remote

Category
Data & Analytics (1)
Required Skills
Bash
Redshift
Python
Airflow
Git
Apache Spark
Apache Kafka
Kinesis
Data Engineering
Infrastructure as Code (IaC)
CloudFormation
AWS
Hadoop
Data Governance
Requirements
  • Professional experience designing, building, and/or operating data engineering or data platform solutions on AWS.
  • Strong experience with AWS data lakes, data pipelines, ETL/ELT, and cloud data architectures.
  • Proficiency in Python and/or Bash.
  • Experience with Spark, Kafka, Airflow, Parquet, Git, and/or Hadoop.
  • Firsthand experience with AWS services including S3, Glue, Lake Formation, Athena, EMR, Kinesis, Lambda, Step Functions, Redshift, IAM, and VPC.
  • Experience with infrastructure-as-code and AWS automation, such as CloudFormation, CDK, or AWS CLI.
  • Strong understanding of data security, governance, quality, monitoring, and operational best practices.
  • Ability to work effectively in a customer-facing consulting environment and communicate complex technical concepts to both technical and business audiences.
Responsibilities
  • Design and implement scalable AWS data architectures, data lakes, and data pipelines.
  • Help customers develop and execute their cloud and data modernization strategies.
  • Build robust data ingestion, transformation, orchestration, and serving solutions for batch and streaming data.
  • Develop reusable frameworks for data ingestion, processing, monitoring, logging, alerting, and error handling.
  • Implement data quality, governance, security, and lifecycle management solutions.
  • Design and optimize Amazon S3 storage, partitioning, encryption, lifecycle policies, and data organization strategies.
  • Leverage AWS-native services such as Glue, Lake Formation, Lambda, Step Functions, Kinesis, EMR, Athena, Redshift, and S3.
  • Develop automation and infrastructure using CloudFormation, AWS CDK, and AWS CLI.
  • Partner directly with customers to translate business and technical requirements into effective solutions.
  • Create technical content including reference architectures, automation tools, technical briefs, case studies, and thought leadership.
  • Stay current with AWS technologies and emerging data engineering practices and bring innovative ideas to customers and the team.

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