Data Engineer, Specialist

Responsibilities

• 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

Requirements

• 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

Qualifications

• Preferred: Experience with AWS Glue, PySpark, Athena, Dremio, Parquet
• Exposure to BI and visualization tools such as Tableau, Power BI, or Streamlit
• Familiarity with Jira, GitHub, ServiceNow, or technology operations data
• Interest in building reusable data products and enabling self-service analytics
• Exposure to AI/ML concepts, LLMs, or agent-based tools to enhance data engineering workflows and automation