Back
Mid-level generalist data role, metro location, and broad AWS/Python/Terraform requirements increase competition.
Data engineering skills are transferable across industries but require cloud and tooling familiarity.
Explicit 5+ years and mandatory AWS, Python, SQL, and Terraform skills require strict filtering.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and operate ETL/ELT data pipelines using Python (Pandas) to meet strict SLOs for freshness, latency, and completeness.
Architect and manage AWS cloud data infrastructure (S3, Glue, Athena) focusing on scalability, performance, resiliency, and cost optimization.
Implement infrastructure as code with Terraform and automate CI/CD pipelines including security scans and deployment, ensuring security-first practices throughout SDLC.
Minimum 5 years of hands-on data engineering experience with production-grade ETL/ELT pipelines.
Strong Python programming skills with proven experience using Pandas library for data manipulation.
Advanced SQL proficiency in PostgreSQL and Trino, including dimensional modeling experience.
Experience managing AWS data services (S3, Glue, Athena) and infrastructure as code using Terraform.
Must be able to join within 30 days (Notice Period).
Experienced in delivering data engineering solutions in Agile environments with a focus on measurable SLOs and security governance.
Skilled at collaborating cross-functionally to translate business requirements into scalable technical solutions and dashboards (e.g., Superset).
Comfortable leveraging AI-assisted development tools and integrating automated security and vulnerability management into CI/CD pipelines.