Create and maintain data pipelines for key data and analytics capabilities in the enterprise
Collaborate within an agile, multi-disciplinary team to develop optimal data integration and transformation solutions
Document and analyze data requirements (functional and non-functional) to develop scalable, automated, fault-tolerant data pipeline solutions for business and technology initiatives
Profile data to assess the accuracy and completeness of data sources and work with business partners to mitigate issues
Build and maintain data pipelines using appropriate tools and practices in development, test, and production environments
Design with modularity to leverage reuse of code wherever possible
Create data mappings, programs, routines, and SQL to acquire data from legacy, web, cloud, and purchased package environments into the analytics environment
Use a mix of ELT, ETL, data virtualization, and other methods to optimize the balance of minimal data movement against performance
Maintain metadata management processes and documentation
Monitor data quality to detect emerging issues and consult with the team to create transformation rules to cleanse against defined rules and standards
Participate in code reviews and unit testing to optimize performance and minimize issues.

Bachelor’s degree in computer science, data science, statistics, economics, or related functional area; or equivalent experience
4+ years’ experience working in a development team providing analytical capabilities
4+ years of hands-on experience in the data space spanning data preparation, SQL, integration tools, ETL/ELT/data pipeline design
SQL coding experience
Familiarity with agile development environments (Scrum, Kanban) with a focus on Continuous Integration and Delivery
Previous experience using a data integration platform (IBM InfoSphere DataStage, Oracle Data Integrator, Informatica PowerCenter, MS SSIS, AWS Glue, Denodo)
Familiarity with data warehouse MPP platforms such as Snowflake, Netezza, Teradata, Redshift, etc.
Familiarity with event store and stream processing (Apache Kafka and platforms like Confluent)
Knowledge of API development and management platforms (MuleSoft, Axway) is also beneficial
Capable of focusing on specific tasks while ensuring alignment to a broader strategic design
Exhibits traits of a proactive, self-driven contributor who values continual learning and adoption of new technology.

Data Engineer – Snowflake, DataStage

Key skills