Data Engineer (Snowflake/DataStage)

VSP Vision Care•Town of Owego, NY

3d•$58,800 - $101,850•Hybrid

About The Position

The Data Engineer creates and maintains data pipelines for key data and analytics capabilities in the enterprise. This position works in collaboration with analytics and data warehousing staff, DBAs and subject matter experts to create reliable processes that load targeted data with integrity and quality, enabling it for strategic use by the business. 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 for 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.

Requirements

Bachelor’s degree in computer science, data science, statistics, economics, or related functional area; or equivalent experience
Effective written and verbal communication skills with the ability to gather requirements and effectively collaborate with teammates and business partners
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), and familiarity with data warehouse MPP platforms such Snowflake, Netezza, Teradata, Redshift, etc.
Capable of focusing on a specific set of tasks while also ensuring alignment to a broader strategic design
Exhibits the traits of a proactive, self-driven contributor, who values continual learning and the adoption of new technology
For roles that are remote (i.e., Work From Home (WFM)) or hybrid (i.e., partial onsite at a VSP location and WFM), must demonstrate a high level of engagement in virtual environments, including maintaining camera presence during meetings to support effective communication and team alignment

Nice To Haves

Strong experience with Snowflake (data modeling, performance tuning, optimization) or certification
Hands-on experience with IBM DataStage
Understanding of Data Vault modeling (Raw Vault, Business Vault, Information Marts)
Experience with workflow orchestration tools (e.g., Apache Airflow)
Proficiency with GitHub (version control, CI/CD, code reviews)
Familiarity with DataOps practices
Experience with streaming technologies (e.g., Kafka/Confluent) and APIs (e.g., MuleSoft, Axway)
Exposure to cloud platforms (AWS, Azure, or GCP)
Familiarity with event store and stream processing (Apache Kafka and platforms like Confluent) and with API development and management platforms (MuleSoft, Axway) is also beneficial

Responsibilities

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 for 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