Popular, Inc. - Charlotte, NC

posted 2 months ago

Full-time - Mid Level
Charlotte, NC
5,001-10,000 employees

About the position

At Popular, the Data Governance Manager II plays a crucial role within the Enterprise Data & Analytics function, focusing on the design and maintenance of data models that support the firm's data management and analytics objectives. This position requires collaboration with data architects, data analysts, and various business units to create data models that ensure data integrity, accuracy, and compliance with financial regulations. The Data Governance Manager is responsible for translating complex financial data into structured formats suitable for analysis, reporting, and decision-making. In this role, you will lead and enhance data models that are essential for the financial firm's data management, analytics, and reporting initiatives. You will work closely with senior data architects and business units to understand their data requirements and convert them into high-quality data models. Ensuring compliance with financial regulations and data governance policies is a key responsibility, as is optimizing data models for integrity, accuracy, and consistency. You will also be tasked with selecting and implementing advanced data modeling tools and methodologies, thoroughly documenting data models, and collaborating with the Senior Data Modeling Lead to align models with the firm's overall data strategy. Additionally, you will ensure the smooth integration of data models into data warehousing, reporting, and analytics solutions, providing critical input to data governance teams to ensure alignment with policies and standards. Your work will involve developing conceptual, logical, and physical data models, as well as data flows and source-to-target mappings, all of which are vital for the success of the organization’s data initiatives.

Responsibilities

  • Lead and enhance data models that support the financial firm's data management, analytics, and reporting initiatives.
  • Work with senior data architects, data analysts, and business units to understand data requirements and convert them into top-tier data models.
  • Ensure data models comply with all financial regulations, data governance policies, and industry standards.
  • Check and optimize data models for data integrity, accuracy, and consistency.
  • Lead the choice and implementation of cutting-edge data modeling tools and methodologies.
  • Thoroughly document data models, including data dictionaries, data lineage, and metadata.
  • Collaborate with the Senior Data Modeling Lead to align data models with the firm's overall data strategy.
  • Ensure the smooth integration of data models into data warehousing, reporting, and analytics solutions.
  • Provide key input to data governance teams to ensure that data models align with data governance policies and standards.
  • Work with the business team to develop conceptual, logical data models, physical data model, data flows, data designs and source-to-target data mapping.

Requirements

  • Bachelor's or master's degree in information management, Computer Science, Data Science, or a related field.
  • 10+ years of experience in data modeling and data architecture including at least 5 years in a leadership or management role with strong understanding of data architecture and data governance principles and practices.
  • Solid experience in data warehousing, BI & Analytics and designing data products.
  • 10+ years of experience in data modeling practices including conceptual, logical, physical modeling in varied data modeling patterns such as 3NF, Data Vault 2.0 and dimensional modeling, with the ability to apply these skills at both project and enterprise levels.
  • Solid experience in dimensional modeling with a proven track record of designing conformed dimensions that are applicable across various Business Units.
  • Solid experience in data modeling tools such as PowerDesigner, IBM Data Architect, Oracle Designer, or Erwin.
  • Strong Financial and Insurance industry domain knowledge.
  • Strong experience in data governance and data management and using tools such as Alation, Collibra, Informatica, Atlan, IBM IGC.
  • Strong experience working in data lake, data lake house, data warehouse, data mesh, and operational data stores.
  • Experience designing models to be leveraged for data as a product and data marketplace.
  • Proficiency in developing data designs, data mapping and data flow logic to support the implementation of data structures designed.
  • Strong experience in a metadata field of work (ontology, taxonomy, semantics, or computational linguistics).
  • Strong experience or training in using W3C standards including linked and canonical data and ontologies (JSON, XML, RDF, RDFS, OWL, and SKOS).
  • Strong experience in ontology and linked data tools (Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World).
  • High proficiency in data analysis and profiling using SQL and Python.
  • Strong experience with cloud platforms such as AWS, Azure, GCP and analytical data stores: Data Lake, Snowflake, Redshift, Hadoop.
  • High proficiency in relational databases and data structures, including structured and unstructured data formats.
  • Experience with working with data integration tools such as Informatica, Talend, CloverDX, DBT.
  • Proficiency in reporting tools such as Tableau and PowerBI.
  • Experience in technology assessment and proven ability to make recommendations to senior members of the team.
  • Strong understanding of data privacy laws and regulations including knowledge on FCRA, CRA, GLBA, Data Privacy rules in addition to CCPA and GDPR.
  • Experience collaborating with IT, Data Analytics, and Business teams, contributing to cross-functional projects and initiatives.
  • Proficiency in Agile-based development methodologies, including Scrum and Kanban for collaborating, developing, and delivering data products.
  • Excellent communication, collaboration, and problem-solving skills.
  • Proven leadership skills with experience in influencing and directing a team.
  • Strong analytical and time management skills.

Nice-to-haves

  • Experience in technology assessment and proven ability to make recommendations to senior members of the team.
  • Strong understanding of data privacy laws and regulations including knowledge on FCRA, CRA, GLBA, Data Privacy rules in addition to CCPA and GDPR.
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