Sr Data Engineer

Key Skills

AWS, Azure, Continuous Integration & Continuous Delivery - CI/CD, Data Engineering, Data Governance, Data Modeling, Data pipelines, Data science techniques, Databricks, Design, Google Cloud Platform (GCP), KPI, Microsoft Office suites, Python Programming, Salesforce, Snowflake, SPARK Programming, SQL

Job Description

This role will be embedded on a cross-functional product Agile scrum team as the primary data engineer. Work with Data Architect(s) and other DAI personnel and takes the lead to develop and maintain data flows, data workflows and other code/logic to gather, create and deliver high quality reliable data to meet the needs of Pella’s business. These efforts will support Pella’s analytics and transactional needs. Additionally, this position will support Pella’s Data Enablement Technologies and Data Users with on-call responsibilities, direct end-user tickets and addressing performance or quality issues.

ESSENTIAL RESPONSIBILITIES:

• Design and develop data pipelines to manage how data flows between disparate systems
• Build data pipelines to feed analytics use cases, KPI or enterprise apps.
• Develop data quality metrics and performs QC tests (system and visual) to verify data integrity.
• Interface with architects, product managers/SMEs and product analysts to understand data needs and support the implementation of the business rules into transformation.
• Document the data blending process along with the specifications and workflow/data lineage.
• Perform continuous integration to ensure that every step of the pipeline is testable and automated
• Lead cloud data migration, transformation and modeling projects, developing project plans and communicating project status through Agile process and in Jira for the cross-functional team
• Collaborate with the business to understand backlog and refine use cases related to data management, BI reporting and data science deliverables. Research source system data, architecture and transactions.

Takes lead to perform detailed design (the Physical Data Model and transformations), based on understanding of the Logical Data Model (the business requirements)

• Create design documents for data integration or data reporting projects
• Develop new and improve existing processes to ensure service levels are being met
• Support development of new or modify existing analytical reports
• Analyze data integration problems, provide solutions and recommend corrective actions.
• Analyze source system data structures and map them to target data warehouse schemas.

• Must have excellent skills in requirements analysis, logical/physical modeling, data transformation and data modeling and technical governance design concepts.

• Serve as a technical expert to data warehouse project teams and key business individuals for support of applications, tools, data integration, and ad-hoc analytics.

• Participate in design and code reviews, documentation of design, and implementation of methodologies to ensure high quality deployments

• Analyze application and data integration problems, provide solutions and recommend corrective actions.

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EDUCATION/EXPERIENCE

• BS degree in Computer Science, Data Engineering, Software Engineering, or a related field. MBA beneficial.
• 5+ years' experience in data engineering / software development

QUALIFICATIONS:

Technical / functional skills (includes computer skills):

• Expertise in Azure cloud technologies specifically Synapse, ADF, Delta Lake, Databricks or comparable technology experience within AWS, Snowflake and/or GCP
• Experience working with architectural fabric of Salesforce or comparable CRM applications
• Understanding of architecture of Data Quality, Metadata Management and Master Data Management

• Understanding of Data Governance and Data Stewardship concepts

• Understanding of dimensional data modeling and design as well as data population techniques for target structures such as Star Schemas.
• Skilled in Python, SPARK and SQL to build production-grade data pipelines and tools
• Experience navigating a modern data environment and working between on-prem & cloud technologies
• Knowledge of the data science process and understanding of/experience with Data Engineering support for Data Science
• Strong grasp of CI/CD operating practices
• Experience operating within a Product Scrum Agile team
• Experience with MS Office, Outlook, Jira

Leadership Skills: Strong communication and collaboration skills, good project management methodology

Certifications or licenses: None

Travel Expected: 5-10% of time