The Data Engineer will be responsible for architecting, designing, and implementing advanced analytics capabilities. The right candidate will have broad skills in database design, be comfortable dealing with large and complex data sets, have experience building self-service dashboards, be comfortable using visualization tools, and be able to apply your skills to generate insights that help solve business challenges. We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level.
Requirements- 12+ years of overall industry experience specifically in data engineering with a heavy focus on the AWS Cloud stack and AI.
- 8+ years of experience building and deploying large-scale data processing pipelines in a production environment.
- Advanced proficiency in Python, SQL, and PySpark.
- Creating and optimizing complex data processing and data transformation pipelines using python
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
- Deep experience with Snowflake/Databricks on AWS, dbt, and distributed computing frameworks like Apache Spark.
- Understanding of Datawarehouse (DWH) systems, and migration from DWH to data lakes/Snowflake
- Understanding of ELT and ETL patterns and when to use each. Understanding of data models and transforming data into the models
- Strong analytic skills related to working with unstructured datasets
- Build processes supporting data transformation, data structures, metadata, dependency and workload management
- Experience supporting and working with cross-functional teams in a dynamic environment
BenefitsSignificant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
