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.