Data Engineer

• Design and implement tailored data solutions to meet customer needs and use cases, spanning from streaming to data lakes, analytics, and beyond within a dynamically evolving technical stack. 

• Provide thought leadership by recommending the most appropriate technologies and solutions for a given use case, covering the entire spectrum from the application layer to infrastructure. 

• Demonstrate proficiency in coding skills, utilizing languages such as Python, Java, and Scala to efficiently move solutions into production while prioritizing performance, security, scalability, and robust data integrations. 

• Collaborate seamlessly across diverse technical stacks, including Cloudera, Databricks, Snowflake, and AWS. 

• Develop and deliver detailed presentations to effectively communicate complex technical concepts. 

• Generate comprehensive solution documentation, including sequence diagrams, class hierarchies, logical system views, etc. 

• Adhere to Agile practices throughout the solution development process. 

• Design, build, and deploy databases and data stores to support organizational requirements. 

Basic Qualifications: 

• 4+ years of experience supporting Software Engineering, Data Engineering, or Data Analytics projects.  

• 2+ years of experience leading a team supporting data related projects to develop end-to-end technical solutions.  

Preferred Skills: 

• Demonstrate production experience in core data platforms such as Snowflake, Databricks, Azure. 

• Showcase professional written and verbal communication skills to effectively convey complex technical concepts. 
• Develop and maintain ETL/ELT pipelines, queries, and transformations in Snowflake (and, as needed, Databricks notebooks or jobs) according to agreed design patterns and metadata driven data pipeline frameworks. 

• Implement medallion-layered data structures and reusable components that can be leveraged across multiple data products and domains.

• Assist in onboarding new data sources, mapping source data to target models, and applying data quality and monitoring rules

• Participate in daily standups, sprint ceremonies (if applicable), and ad hoc working sessions

• Undergraduate or Graduate degree preferred