Note: The job is a remote job and is open to candidates in USA. VSP Vision is a company focused on providing data-driven insights and solutions, and they are seeking a Data Engineer to create and maintain data pipelines for analytics capabilities. This role involves collaborating with various teams to ensure data integrity and quality while developing scalable and automated data solutions.
Responsibilities
- 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 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
Skills
- 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
- 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
- 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
- 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)
Benefits
- This role may include eligible bonuses and commissions
- For more information regarding VSP Vision benefits, please click here (http://www.vspvision.com/careers/rewards-and-benefits.html)
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