Senior Data Engineer

Responsibilities:

• Partner with technical and non-technical colleagues to understand data and reporting requirements.
• Work with engineering teams to collect required data from internal and external systems.
• Design table structures and define ETL pipelines to build performant data solutions that are reliable and scalable in a fast-growing data ecosystem.
• Develop data quality checks.
• Develop and maintain ETL routines using ETL and orchestration tools such as Airflow.
• Implement database deployments using tools like Schema Change.
• Perform ad hoc analysis as necessary.
• Perform SQL and ETL tuning as necessary.

Requirements:

• 5+ years of relevant data engineering experience.
• Strong understanding of data modeling principles, including dimensional modeling and data normalization principles.
• Good understanding of SQL engines and ability to conduct advanced performance tuning.
• Ability to think strategically, analyze, and interpret market and consumer information.
• Strong communication skills; written and verbal presentations.
• Excellent conceptual and analytical reasoning competencies.
• Comfortable working in a fast-paced and highly collaborative environment.
• Familiarity with Agile Scrum principles and ceremonies.
• Bachelor's degree in computer science, information systems, or a related field or equivalent work experience.

Preferred Qualifications:

• 2+ years of work experience implementing and reporting on business key performance indicators in data warehousing environments, required.
• 2+ years of experience using analytic SQL, working with traditional relational databases and/or distributed systems (Snowflake or Redshift), required.
• 1+ years of experience with programming languages (e. g., Python, PySpark), preferred.
• 1+ years of experience with data orchestration/ETL tools (Airflow, NiFi), preferred.
• Experience with Snowflake, Databricks/EMR/Spark, and/or Airflow.