Design, build, and maintain scalable ETL/ELT pipelines for critical IT data sources
Develop curated, high-quality datasets to support reporting, dashboards, and analytics products
Write, optimize, and maintain SQL and Python code for transformation, automation, and performance
Deliver cloud-based data solutions using AWS services such as Glue, S3, and Athena
Partner with analysts, product managers, and stakeholders to translate data needs into practical solutions
Implement data quality checks, validation rules, monitoring, and documentation to ensure trusted data
Troubleshoot pipeline issues, investigate anomalies, and resolve data defects end-to-end
Apply engineering best practices including version control (Git), code reviews, testing, and CI/CD deployment
Contribute to standards for data lineage, governance, documentation, and production support
Support the evolution of reusable data products and self-service analytics capabilities

Bachelor’s degree or equivalent combination of education and relevant experience
3–5+ years of experience in data engineering, analytics engineering, or data platform development
Strong proficiency in SQL and Python for data transformation and automation
Hands-on experience building and supporting ETL/ELT pipelines
Experience with AWS or similar cloud data platforms
Solid understanding of data modeling, curated datasets, and BI/reporting use cases
Demonstrated problem-solving skills and commitment to data quality and reliability
Ability to communicate effectively with both technical and non-technical stakeholders
Experience working in collaborative, agile team environments

Data Engineer – Specialist

Key skills