Head of Data Engineering and Operations

4 weeks ago

Edmonton Division No, CA Equifax, Inc. Full time

Synopsis of the role

The Head of Data Engineering and Operations is the organizational thought leader for the management of Data at Equifax. Leveraging data fabric as an enabler for business transformation, this leader is responsible for designing high level data architecture, end-to-end data pipelines, and optimizing search match logic. In conjunction with the Data team, this role will play a critical role in the overall data strategy by staying current on emerging trends and innovation in modern data management methods. Reporting to the Chief Data Officer, and working closely with IT, the Data Engineering and Operations leader will be responsible for designing and implementing new data architecture that leverages our investment in Cloud technology, including the development of alternate data exchanges within our data fabric, and building more flexible tools to ingest and leverage a broader range of data assets . To support the growth in our data assets and in close collaboration with the Data Acquisition team, the Head of Data Engineering and Operations will lead a small group of data scientists that are tasked with testing the value of new data sources and identifying key trends within our current assets. To support the robust data environment, this role will work closely with Data Governance, ensuring that there is clear yet nimble oversight, governance and processes to ensure the protection and consistency of our data assets.

What You’ll Do

  • Design and build new data structures to maximize the value of our Cloud-based data fabric to expand into new data sources

  • Collaborate closely with Data Acquisition to understand the overall data strategy and support through developing strong data architecture plans

  • Leverage data scientists to identify opportunities to improve the data, increase match rates and find potential patterns across the assets

  • Work with Data Contributor Services to understand new data ingestion models using Cloud-technology in support of alternate data furnishers

  • Ensure a strong, documented data environment is in place leveraging our Collibra platform, including metadata, a business-driven data catalogue, and data lineage

  • Bridge the gap between data ingestion and product development to create reusable, nimble and efficient data pipelines.

What Experience you need (5 or less requirements)

  • A strong understanding of data-driven, technology based product development with 5 to 7 years of hands-on experience designing and building analytical solutions to solve real world problems.

  • Strong knowledge of Cloud-based capabilities and platforms (Google cloud an asset)

  • Experience in analytics, software engineering, data management/architecture or similar and experience in managing technical documentation

  • Strong knowledge of Big Data platforms such as Hadoop and the associated tools needed for analytics and a good understanding of modern data architecture, data security, and design principles

  • Knowledge of analytical techniques including decision trees, logistic regression, and, preferably, machine learning methodologies

  • Strong understanding of agile methodologies including the creation of epics and user stories

What could set you apart

  • Experience in large scale digital transformation initiatives

  • Expertise in the financial services industry

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