Here at Wilson Language Training, we are committed to working together for our mission to achieve literacy for all. We believe literacy is a fundamental right and should be attainable for all people. We strive to reflect this belief in our work.
The success of our team members is no less paramount. We’re dedicated to ensuring that every Wilson employee experiences truly satisfying professional development while feeling inspired to bring their authentic selves to work. Are you ready to be a changemaker?

Wilson Language training is growing and is looking to hire a Data/Analytics Engineer.

As an Analytics Engineer you will bridge the gap between data engineering and data analysis. You will be responsible for building and maintaining robust data pipelines, transforming raw data into actionable insights, and collaborating with various teams to support data-driven decision-making.

Key Responsibilities:

• Data Pipeline Development: Design, develop, and maintain scalable data pipelines to ingest, process, and store large volumes of data from various sources.
• Data Modeling: Create and manage data models to support analytics and reporting needs, ensuring data accuracy and consistency.
• ETL Processes: Implement ETL (Extract, Transform, Load) processes to ensure the smooth flow of data from source systems to data warehouses.
• Collaboration: Work closely with data analysts and business stakeholders to understand data requirements and deliver data solutions that meet their needs.
• Data Quality: Implement data quality checks and monitoring to ensure the reliability and accuracy of data.
• Optimization: Optimize data processing and storage for performance and cost efficiency.
• Documentation: Maintain comprehensive documentation of data pipelines, models, and processes.
• AdHoc Querying & Data Integrations: Assist Business Systems team with adhoc querying and reporting from ERP/CRM systems. Help with data integrations between these systems and our custom built applications.
• Innovation: Stay up-to-date with industry trends and best practices in data engineering and analytics, and apply them to improve existing processes.
• Understand and display WLT’s values.
• Other duties as assigned

Qualifications:

• Education: Bachelor’s degree in Computer Science, Data Science, Information Technology, or a related field. A master’s degree is a plus.
• Experience: 3+ years of experience in data engineering, analytics, or a related field.
• Technical Skills: Proficiency in Microsoft SQL, dBT, Python, and/or R. Experience with data pipeline tools (e.g., Apache Airflow, Luigi) and data warehousing solutions (Azure SQL, Azure Fabric, Azure Synapse).
• Tools: Familiarity Microsoft Power BI.
• Cloud Platforms: Experience with cloud platforms like Azure Fabirc.
• Problem-Solving: Strong analytical and problem-solving skills with a keen attention to detail.
• Communication: Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Knowledge of machine learning and predictive analytics.
• Experience with version control systems (e.g., Git).
• Understanding of data governance and security best practices.

Wilson has identified the anticipated pay range for this role based on the many factors that we consider in defining compensation levels for our roles, including market data, and internal equity considerations. Actual pay, and allocation between base and any target discretionary bonus, will vary based on geographic location, education, work experience, skills, market data, and internal equity considerations. Wilson offers competitive benefits, including:

• Medical, dental, vision, and Life & Disability Insurance
• 401k plan with partial employer match
• Paid Time Off
• Paid holidays
• Tuition reimbursement
• “O’Connor days,” which refers to a company-wide office closure between Christmas and New Year’s Eve, as well as other perks.

Anticipated Salary range: $117,000 - $152,000.

Wilson Language Training is an Equal Opportunity, Drug-Free Employer Committed to Diversity in the Workplace. M/W/D/V