Junior Data Engineer

Role Responsibilities

• Design, develop, test, and maintain scalable ETL/ELT pipelines and data integration solutions using SQL, Python, and cloud-native services
• Develop and optimize SQL queries, stored procedures, transformations and data pipelines
• Design and maintain analytics-ready data models for reporting, dashboards, and downstream applications, including dimensional and semantic modeling patterns
• Integrate data from databases, flat files, APIs, and third-party systems into governed, reusable datasets
• Monitor, troubleshoot, and tune data pipelines and database workloads for reliability, performance, and cost efficiency
• Establish and maintain data quality controls, including profiling, validation, testing, reconciliation, monitoring, and alerting
• Operationalize pipelines using CI/CD practices, code review, and environment promotion processes
• Implement and support orchestration, scheduling, and observability for batch and near-real-time data workflows
• Support cloud adoption and modernization efforts, including migration of legacy or on-premises data workflows to cloud environments
• Model and serve data for analytics and BI use cases, including support for Power BI data sets, row-level security, and refresh orchestration
• Document data lineage, architecture, and data contracts, contributing to metadata/catalog solutions (e.g., Microsoft Purview)
• Collaborate within a Scrum team, participating in sprint ceremonies and refining user stories with stakeholders
• Work with business users to gather and translate functional and technical requirements
• Provide technical assistance and support to education stakeholders (remote and/or on-site)
• Continuously improve processes through automation, standardization, and best practices

Qualifications

• Five years experience designing, building, and supporting SQL-based ETL/ELT and data integration solutions
• Advanced SQL skills, including complex transformations, performance tuning, and working with large datasets
• Experience with Python for data engineering, automation, data transformation, or data quality workflows
• Strong experience with data modeling for analytics and reporting, including schema design and dimensional modeling
• Hands-on experience with cloud data platforms and services; Azure preferred, with AWS or GCP experience also valued
• Experience helping modernize or migrate data workloads from legacy or on-premises environments to the cloud
• Experience with orchestration, scheduling, or workflow automation for production data pipelines
• Experience with version control (Git) and CI/CD pipelines (e.g., Azure DevOps)
• Knowledge of data architecture principles (e.g., lakehouse patterns, partitioning, schema design, performance tuning)
• Experience with automated testing (unit/integration testing for data solutions)
• Strong understanding of data governance, quality, and lineage concepts
• Excellent communication, organizational, and time management skills
• Experience working collaboratively in Agile/Scrum environments
• Familiarity with AI-assisted development tools and/or applying generative AI to improve data engineering, documentation, or analytics workflows