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.