Leverage analysis and design techniques to solve business problems using information technology to operationalize data and analytical models and drive long-term business results. Experience in data modeling and wrangling techniques and tools, including Star Schema, Snowflake Schema, Data Vault, Alteryx, Power BI, Tableau, etc.
Numbers & Facts
Location
East Hanover, NJ (Remote)
Salary
$40–$41.40 Per Hour
Description
Summary:
Work Mode: Remote
Hours: 8:00 AM - 5:00 PM
Responsibilities:
Leverage analysis and design techniques to solve business problems using information technology to operationalize data and analytical models and drive long-term business results.
Partner with MDS to ensure accessibility, retrievability, security, and protection of data ethically.
Collaborate with Product Owners, BI Developers, and Business Leads to gather business requirements and support continuous improvement sessions.
Develop UAT (User Acceptance Testing) and SIT (System Integration Testing) test cases based on analytical data product requirements.
Support the scoping, building, testing, and maintenance of transport/data pipelines and retrieval of applicable data sets for specific use cases.
Support the building, testing, and maintenance of data models with flexibility for changing business requirements.
Analyze the structure, format, and reliability of new and existing data sources to drive continuous improvement.
Participate in data governance processes to ensure data is properly maintained and documented for reusability.
Understand data and metadata to support consistency of information retrieval, combination, analysis, pattern recognition, and interpretation.
Requirements:
Understanding of Data Engineering concepts within a business setting, including working with multiple systems such as SAP and internal and external data sources.
Experience in developing, enhancing, testing, and maintaining data products.
Proficiency in using a diverse range of languages and tools for data extraction, transformation, storage, processing, and integration.
Ability to analyze business requirements for data modeling and apply data analysis, design, modeling, and quality assurance techniques.
Ability to simplify complex problems and communicate technical concepts to a diverse audience.
Preferred Skills:
Experience with cloud computing technologies: Azure, GCP.
Proficiency in programming languages: SQL, Python, PySpark (Apache Spark), DAX, etc.
Familiarity with analytics platforms: Databricks, Google Cloud Dataproc, etc.
Experience with CI/CD, DevOps, and DataOps techniques.
Experience with ETL, data pipelines, and architecture.
Technical documentation skills.
Experience in data modeling and wrangling techniques and tools, including Star Schema, Snowflake Schema, Data Vault, Alteryx, Power BI, Tableau, etc.
Knowledge of data quality and profiling methods.
Education / Certifications:
Bachelor’s degree in a related field.
BS in Computer Science, Information Systems, etc.
Job-Specific Requirements:
Minimum 1 year of Data Engineering/Modeling experience.