Senior Engineer Data Engineering

What You'll Do -------------- * Design and implement **data models** and database structures to support scalable and efficient data solutions. * Develop and optimize **ETL processes** to ensure seamless data integration and transformation. * Utilize **SQL** and database optimization techniques to enhance query performance and data retrieval. * Leverage **cloud data platforms** (e.g., Snowflake) to build and maintain robust data architectures. * Partner with stakeholders to gather requirements, provide technical recommendations, and deliver data-driven solutions. * Ensure data quality and integrity through validation, testing, monitoring, and issue resolution. * Support project planning, estimation, and delivery in an **Agile environment**. * Mentor junior team members and contribute to knowledge sharing across the team. What You'll Bring ----------------- * **Bachelor’s degree in a relevant field** such as Computer Science, Information Systems, or related discipline. * **4–6 years of relevant experience** in data modeling, ETL development, and database optimization. * Proficiency in **SQL** and experience with **cloud data platforms** like Snowflake. * Strong understanding of **ETL process development** and data integration techniques. * Demonstrated ability in **data modeling and design** for scalable and efficient solutions. * Experience working independently and managing workstreams with limited oversight. * Excellent **stakeholder communication and collaboration** skills. * Familiarity with **Python**, **Pyspark**, or other programming languages for data engineering tasks. * Knowledge of **data warehousing** concepts is a plus. Additional Skills ----------------- * Proficiency in **version control tools** such as Git and GitHub. * **Strong Excel skills**, including functions, PivotTables, and Power Query for data analysis and legacy structures. * Experience with **Power BI or similar BI tools** for data modeling and reporting. * Familiarity with **SQL Server and Azure SQL**, including stored procedures and performance‑oriented queries. * **Strong documentation** practices using Markdown or similar formats for data models, pipelines, and standards.