Data Engineer

The job overview for this role is that the candidate will be responsible for designing, developing, and expanding data assets to support business intelligence, advanced analytics, and reporting. They will also be involved in developing and maintaining the enterprise data warehouse system, data marts, and data interfaces for reporting and analytics purposes. The role requires deep experience in data management and a strong understanding of the data management life cycle. Effective communication and program management skills are also important for success in this role.

Design, develop, and expand data assets that support business intelligence, advanced analytics, and reporting.

Develop, maintain, and support the enterprise data warehouse system, data marts, and data interfaces for reporting, analytics, and applications.

Build solutions to manage core master data and ensure data quality.

Assemble large, complex data sets that meet functional and non-functional business requirements.

Identify and automate manual processes, optimize data delivery, and redesign infrastructure for greater scalability.

Build the infrastructure required for optimal extraction, transformation, and loading of data from various sources into Snowflake.

Create and review technical solution requirements documents.

Align with industry-leading technology standards to develop solution capabilities.

Collaborate with data and analytics experts to enhance functionality in data systems.

Communicate with internal team members and stakeholders in different time zones for requirements clarification and progress reporting.

• 5+ years of experience as a Data Engineer
• Proficiency in object-oriented/object function scripting languages such as Python and Java
• Advanced knowledge of relational SQL and NoSQL databases, including Postgres and Cassandra
• Hands-on experience in implementing MDM (Master Data Management) solution capabilities for Entity Management, Hierarchy Management, Data Cleansing, Match and Merge, etc.
• Familiarity with data modeling (logical, physical data models) and metadata
• Experience in data quality management and analysis
• Ability to build and optimize 'big data' data pipelines, architectures, and data sets
• Knowledge of data pipeline and workflow management tools like Airflow
• Familiarity with AWS cloud services, specifically Aurora and Kinesis
• Experience with stream-processing systems like Spark-Streaming and Kafka
• Proficiency in performing root cause analysis on internal and external data and processes
• Strong analytical skills for working with unstructured datasets
• Ability to build processes supporting data transformation, data structures, metadata, dependency, and workload management

• Ample opportunity to learn, develop yourself, and expand into different roles
• Pure Equality program supporting employee resource groups
• Pure Good Foundation giving back to local and global communities through volunteering and grants
• Flexible time off
• Wellness resources
• Company-sponsored team events
• Equal opportunity and affirmative action employer
• No discrimination based on race, religion, color, national origin, sex, sexual orientation, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or any other legally protected characteristic
• Accommodation for individuals with disabilities available upon request