Data Engineering·Confirmed live in the last 24 hours·
Full-timeRemote in USANo salary listedRemote
About the Job
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 technologies such as 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.
U.S. work authorization is required; candidates must be legally authorized to work in the United States without current or future employer sponsorship.
Responsibilities
Design and implement scalable AWS data architectures, data lakes, and data pipelines.
Help customers develop and execute cloud and data modernization strategies.
Build 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.
Vertical Relevance is seeking an experienced Sr. AWS Data Engineer Consultant to join our team as a full-time, remote employee. In this role, you will design, build, and deploy scalable data solutions on AWS while collaborating directly with customers to modernize their data platforms and cloud capabilities. You will combine strong hands-on engineering skills with consulting and communication abilities to solve complex data challenges, earn customer trust, and deliver measurable business outcomes. What You will Do:
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 our customers and team.
U.S. work authorization required. Candidates must be legally authorized to work in the United States without current or future employer sponsorship.
What You Bring:
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 technologies such as 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.
Excellent communication, collaboration, organization, and critical thinking skills.
Ability to work effectively in a customer-facing consulting environment and communicate complex technical concepts to both technical and business audiences.
A strong sense of ownership, curiosity, and commitment to delivering high-quality outcomes.
Why Vertical Relevance?
At Vertical Relevance, we believe in delivering with excellence through teamwork, automating everything, constantly learning, and taking ownership of customer outcomes.
We help organizations navigate complex transformation initiatives across people, processes, technology, and data. Our team brings deep industry expertise and a practical, results-oriented approach to every engagement.
If you are an AWS data engineer who enjoys solving challenging problems, collaborating directly with customers, and building modern cloud data solutions, we’d love to hear from you.
Vertical Relevance is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by applicable law.