DevOps Engineer

About the role

The role involves designing, building, and maintaining scalable ETL/ELT pipelines across multi-source enterprise data environments. It also includes architecting and implementing CI/CD frameworks for data platform deployments, developing and maintaining governed data lake architectures aligned to Medallion standards, implementing Python/Bash automation libraries for data ingestion, transformation, and regression workflows, supporting cloud modernization efforts on AWS (primary) and Azure, and implementing telemetry and ETL pipelines for KPI tracking, operational dashboards, and reporting.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines across multi-source enterprise data environments
• Arcitect and implement CI/CD frameworks for data platform deployments
• Build and maintain governed data lake architectures aligned to Medallion standards
• Implement Python/Bash automation libraries for data ingestion, transformation, and regression workflows
• Support cloud modernization efforts on AWS (primary) and Azure
• Implement telemetry and ETL pipelines for KPI tracking, operational dashboards, and reporting

Requirements

• 8+ years of data engineering experience with strong DevOps/MLOps fluency
• Hands-on expertise with AWS (S3, Glue, Lambda, Redshift, EMR or equivalent)
• Proficiency in Python, SQL, and Bash scripting
• Experience with CI/CD tooling: Jenkins, GitLab CI, Azure DevOps, Docker
• Solid background in enterprise data modeling 3NF, Dimensional, Data Vault
• Familiarity with modern data platforms: Snowflake, Databricks, or Azure Data Explorer

Qualifications

• Hands-on experience with AWS services
• Strong proficiency in Python, SQL, and Bash
• Experience with CI/CD tools
• Background in enterprise data modeling
• Knowledge of modern data platforms

Skills

• Data Engineering
• DevOps
• MLOps
• AWS Services (S3, Glue, Lambda, Redshift, EMR)
• Python
• SQL
• Bash Scripting
• CI/CD Tools (Jenkins, GitLab CI, Azure DevOps, Docker)
• Enterprise Data Modeling
• Modern Data Platforms (Snowflake, Databricks, Azure Data Explorer)

Benefits

• Opportunity to work on modernizing enterprise data platforms
• Exposure to cutting-edge AI and agentic data strategies
• Collaboration with cross-functional IT, analytics, and supply chain teams

Pay

TBD

Schedule

TBD

Benefits

• Flexible schedule
• Competitive compensation package
• Professional development opportunities
• Health and wellness benefits
• Work-life balance initiatives