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.