Enterprise Data Solutions Engineer

At Skillsoft, we believe skills fuel growth. Our mission is to empower every organization and every learner to turn constant change into continuous growth. As part of the team, your skills will help organizations understand what skills they have, what they need next, and how to apply them in ways that drive real performance and progress. S killsoft are seeking an experienced Data Engineer who is excited to grow in their professional development. This is a hands-on technical role suited for someone who is comfortable writing and debugging code, eager to deepen their expertise in data engineering patterns, and looking to grow toward independent technical ownership over the next one to two years. REPONSIBILITIES: Data Engineering - 60% Develop and maintain ETL/ELT pipelines using PySpark and Python in Databricks Build and extend data transformations across Bronze, Silver, and Gold layers of the medallion architecture Write well-structured, readable, and testable code following team standards and review feedback Troubleshoot and resolve data pipeline failures, with escalation to senior engineers for complex issues Contribute to pipeline documentation including data flow diagrams and inline code comments Write and optimize T-SQL queries, stored procedures, and views in SQL Server Support data loads and transformations that feed the SQL Server data warehouse Assist in identifying and resolving query performance issues with guidance from senior engineers Apply basic indexing knowledge and understand schema design patterns used by the team Data Quality Testing – 30% Write unit tests and data quality checks for pipelines developed or modified Use established data quality frameworks and tooling consistent with team standards Investigate and escalate data anomalies or quality issues found in pipelines Collaboration Communication – 10% Participate in code reviews — both receiving and providing constructive feedback as skills develop Collaborate with teammates during sprint planning, standups, and retrospectives Communicate blockers and progress clearly to your manager and team Work with data analysts and other stakeholders to understand requirements for assigned work SKILLS QUALIFICATIONS REQUIRED: 2–4 years of professional data engineering experience with a Bachelor's degree Proficiency in SQL — comfortable writing multi-table joins, window functions, and subqueries Working knowledge of Python for data processing tasks Exposure to Databricks, Apache Spark, or PySpark in a professional or academic setting Familiarity with cloud data storage concepts; experience with Azure or ADLS a plus Understanding of ETL/ELT principles and data pipeline design Comfort using Git for version control and working within a collaborative branching workflow PREFERRED EXPERIENCE: Hands-on experience with the medallion architecture (Bronze / Silver / Gold) pattern Experience with Delta Lake or similar table formats (Iceberg, Hudi) Familiarity with SQL Server, including T-SQL and stored procedure development Exposure to CI/CD pipelines and automated testing in a data context Experience with a data quality or transformation framework such as dbt or Great Expectations Familiarity with Azure services beyond ADLS (e.g., Azure Data Factory, Azure DevOps) MORE ABOUT SKILLSOFT: Skillsoft (NYSE: SKIL) is a global leader in AI-native skills management for the human + AI era. By unifying learning, real-time skills intelligence, and workforce insights, Skillsoft helps enterprises build their Skillforce™ — humans and AI working together to drive measurable business outcomes. Through personalized, interactive learning across leadership, technology, and compliance, Skillsoft enables organizations to close critical skill gaps and accelerate transformation. Skillsoft is trusted by thousands of organizations worldwide, including 60% of the Fortune 1000, and supports a global community of more than 105 million learners. Learn more at skills ... (truncated, view full listing at source)