Data Integration Specialist

Overview

The Data Integration Specialist position is a client-facing role, working closely with the client’s business and IT data groups to onboard their data onto the Enterra solution(s) and deliver unique high-impact business solutions utilizing advanced technologies. This role will provide data support, validation and analyze/improve data architectures in support of business processes. They will also provide input to the development of Enterra’s solution offerings as a whole and specifically for individual clients.

As a Data Integration Specialist, you will:

• Specify data requirements to the client and understand the data available/received from the client.
• Map the data available with the data requirements to:
  • Identify any gaps, issues and nuances; and determine the impact and design appropriate remedies.
  • Specify the transformation needed to load the client data into the Enterra solution data models.
  • Work with data engineers to ensure the correct implementation of the specifications.
  • Validate the data load process.
• If needed, perform:
  
  • Initial data wrangling to derive and verify mapping to defined metadata and data requirements.
  • Additional data wrangling to support new features at the client and create specifications for inclusion into the product offering.
• Understand any planned upcoming changes that may impact the client data (e.g., creation of a new data lake or other data sources)
• Comprehend and specify the cadence of data refresh needed to support the client deliverables.
• Test the client specific instance of the Enterra business solution.
• Highlight and specify opportunities or gaps within the Enterra data models and offerings.

Requirements:

• Bachelor’s Degree in a STEM (Science, Technology, Engineering or Math) subject.
• Experience in a client-facing/consulting role.
• Experience in data wrangling (harmonization, cleansing, transformation etc.) using Python, Jupyter notebooks or R.
• Excellent verbal and written communication skills. Ability to clearly communicate complex data relationships to both internal and client teams. This includes documentation, presentations, and individual analysis sessions.
• Experience in specifying requirements using different approaches such as use cases, activity diagrams, sequence diagrams and state charts, data dictionaries, class or entity relationship diagrams.
• Distinctive problem-solving and analytical skills, combined with strong business sense.
• Strong proficiency with Microsoft Office (Word, Excel, PowerPoint and Visio).
• Knowledge of data technologies such as Relational Databases, Databricks, Snowflake or similar.