Purpose of the Position:
The purpose of the Senior Data Engineer for Insights and Reporting role is to design and implement data models and architectures that enable business stakeholders to gain insights from large-scale datasets. This individual will work closely with cross-functional teams to understand business requirements and develop solutions that enable data-driven decision making. The Senior Data Engineer will be responsible for designing and developing ETL processes, pipelines, and data validation processes to ensure accuracy and consistency of data. They will also be responsible for developing and maintaining dashboards, reports, and visualizations that provide insights into key business metrics and trends. The purpose of this role is to help organizations leverage their data to make informed decisions and improve business outcomes.

  • Compliance
  • Operational Delivery
  • Technical Leadership
  • Ensure solutions adhere to standards and best practices and participate in solution reviews to ensure all solutions fit within standardsOperate within project environments and participate in CII continuous improvement efforts
  • Design and develop data models, ETL processes, and pipelines to support data ingestion, transformation, and [URL Removed] with cross-functional teams to identify data requirements, prioritize data initiatives, and drive solutions that enable data-driven decision [URL Removed] and maintain dashboards, reports, and visualizations that provide insights into key business metrics and [URL Removed] and implement data quality and data validation processes to ensure accuracy and consistency of [URL Removed] and maintain documentation for data models, data lineage, and data flow.
  • Lead technical delivery within squads and provide oversight of [URL Removed] knowledge and practical experience with [URL Removed] and contribute to development of architectural principals and [URL Removed] and coach junior data engineers to develop their skills and expertise.
  • Qualifications:A Bachelor’s Degree in Computer Science, Information Technology or Equivalent QualificationTechnology Certifications in Databricks, Azure, Data Engineering and other technologies highly advantageous
  • Experience Minimum 5 years’ experience as a Data EngineerProficiency in SQL, Python and other programming languages commonly used in data [URL Removed] with data visualization tools such as Paginated reports (SSRS), Power BI, Tableau or [URL Removed] in developing solutions in cloud technologies including but not limited to Azure, Databricks, SQL and Data LakeExperience with distributed computing systems, such as Hadoop and [URL Removed] in Dimensional Modeling
  • Technical CompetenciesLanguages: Transact SQL PythonSparkScalaTechnologies:Azure Data Factory Azure Synapse AnalyticsAzure DevOpsData LakePower BISQL ServerDatabricks
  • Behavioral CompetenciesAccountability Relationship buildingDetail Orientated Problem SolvingTeamworkInterpersonal SupportPerseveranceMotivationPrioritizationAnalytical Thinking Strong communication and interpersonal skills.

Desired Skills:

  • transact sql
  • python
  • spark
  • scala
  • azure data factory
  • azure synapse analytics
  • azure devops
  • data lake
  • data bricks
  • power bi
  • ssrs
  • tableau
  • qlikview
  • sql
  • sql server

Desired Work Experience:

  • 5 to 10 years Data Analysis / Data Warehousing

Desired Qualification Level:

  • Degree

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