We prefer a hybrid candidate located in NYC but are also open to someone who is 100% remote. Our client is a PE-backed consumer-focused company in the Financial Services space that is gearing up for long-term strategic initiatives centered around the integration of systems/data. They are a conglomerate of many different businesses acquired over the years and are looking to bring everything onto a common platform which will require a plan around Data. This role will be a key cog in accomplishing this and will have tremendous revenue along with business impact. Responsibilities:
- Be responsible for the development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL).
- Oversee and govern the expansion of existing data architecture and the optimization of data query performance via best practices. The candidate must be able to work independently and collaboratively.
- Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
- Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models
- Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.
- Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
- Hands-on modeling, design, configuration, installation, performance tuning, and sandbox POC.
- Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks.
Qualifications:
- Bachelor's or master's degree in computer/data science technical or related experience.
- 10+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
- Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required.
- Good knowledge of metadata management, data modeling, and related tools (Erwin or ER Studio or others) required.
- Experience in team management, communication, and presentation.
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