Design and implement robust, cloud-based data storage solutions, optimizing schemas for multi-tenant environments while ensuring data accessibility and security and a high standard of trust and transparency
Develop, deploy, and maintain resilient ETL/ELT pipelines for both real-time streaming and batch processing, ensuring seamless data flow from raw ingestion to production-ready applications
Build and manage data access layers, including REST APIs and streaming services, to empower downstream users
Drive data governance and best practices: Contribute across teams to recommend tools, processes, and best practices for maintaining data health, integrity, and security
Support AI operations (MLOps) by managing versioning, containerization, and deployment of AI models
Build monitoring and alerting systems to track data health and system performance, proactively identifying and remediating bottlenecks

Requirements

Bachelor’s degree or higher in Computer Science, Engineering, or Data Science
5+ years of professional experience in data engineering or a related role
A strong foundation in Python (or equivalent), including testing frameworks (e.g., pytest) and ORMs (e.g., SQLAlchemy)
You understand modularity and how to define clear scopes and responsibilities within a large codebase
Proven experience architecting scalable relational and non-relational (SQL/noSQL) schemas
You manage the end-to-end database lifecycle, from initial design to production maintenance
Expertise in maximizing system performance through advanced query tuning, strategic indexing, and execution plan analysis to eliminate technical bottlenecks
Experience with one or more cloud-based databases (e.g., AWS RDS, Azure Database)
You are comfortable configuring compute resources, backups, and geolocation requirements
Experience building resilient pipelines using frameworks such as Dagster or Apache Airflow
You have a track record of maintaining data health for both real-time streaming and batch processing
A strong understanding of how data infrastructure integrates into the broader application architecture
Experience with modern software development practices, including version control (Git), CI/CD pipelines, and a commitment to high-quality, maintainable code .

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonETLELTREST APIsMLOpsSQLnoSQLquery tuningstrategic indexingApache Airflow

Soft Skills

data governancecollaborationproblem-solvingmodularitycommunicationproactive identificationresponsibility definitionbest practicesdata integritytrust and transparency

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in EngineeringBachelor’s degree in Data Science