Senior Data Engineer- Full Time Role

Maveric Systems Limited; Denver (CO); On-site; USD 120,000 - 170,000; Full time

Job summary

Maveric Systems Limited is seeking a Data Platform Engineer to design, build, and optimize scalable data pipelines on AWS. You will implement batch and near real-time processing using Spark and develop data models for analytics and reporting.

The role focuses on ETL/ELT development, data governance, and ensuring data quality across multiple source systems, with collaboration across architects and application teams.

Qualifications

• Experience designing data platforms on AWS.
• Strong ETL/ELT implementation experience.
• Proficient in data modeling for analytics and reporting.

Responsibilities

• Design, develop, and maintain scalable data platforms and pipelines on AWS.
• Implement batch and near real-time data processing using Spark.
• Build and optimize ETL/ELT pipelines from multiple sources.

Skills

Data pipelines

ETL/ELT development

Data modeling

Data quality

Data governance

Cloud architecture

Collaboration

Performance tuning

Tools

AWS Glue

Apache Spark

PostgreSQL

AWS S3

AWS Lambda

IAM

CloudWatch

Redshift

Job description

• Design, develop, and maintain scalable data platforms and pipelines on AWS.
• Implement batch and near real-time data processing solutions using AWS Glue and Apache Spark.
• Develop and optimize data models to support analytics, reporting, and downstream applications.
• Build and maintain ETL/ELT pipelines from multiple source systems.
• Design and develop database solutions using PostgreSQL.
• Leverage AWS services such as S3, Glue, Lambda, IAM, CloudWatch, and Redshift as part of data platform implementations.
• Collaborate with architects, business analysts, and application teams to define data requirements.
• Perform data quality validation, reconciliation, and performance tuning.
• Support migration initiatives from legacy databases such as Microsoft SQL Server to cloud-native solutions.
• Implement data governance, security, and operational best practices.