About
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
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Languages
- English
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