Data Architect - Banking / Credit / Financial Services @ Dataplatr Inc. | Jobright.ai
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Dataplatr Inc. ยท 2 days ago

Data Architect - Banking / Credit / Financial Services

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Responsibilities

Develops and maintains system architectures for specific business areas in compliance with applicable enterprise architectures
Provides oversight on the architecture and design of specific systems within a line of business
Participates in assignments concerning development of target conceptual and logical architectures for products and solutions
Participates in reviews to evaluate and ensure that the architecture meets policies, principles, standards, and business/technology needs and roadmaps.
Reviews and aligns system choices to ensure that enterprise architecture standards, service quality and availability, and cost efficiency are met.
Maintains knowledge of emerging technology trends and utilizes this knowledge to design innovative solutions that support and drive business objectives and technology roadmaps.
Contributes to the definition and analysis of requirements for the system and applying available and emerging technologies to support tactical and strategic business objectives.
Researches and recommends changes to foundational/target architectures.
Evaluates products and technologies and their alternatives for use in individual systems.
Maintains a strong understanding of the enterprise's IT systems and architectures.
Performs other duties as assigned.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data management systemsBanking experienceData warehousingCloud PlatformsModern data architecturesBusiness intelligence toolsSQLNoSQLJavaPythonC/C++Data science languagesEntity-relationship modelingData quality toolsSolution designMachine Learning/AICollaboration skills

Required

Prior experience with Banking/Credit/Financial services is a MUST HAVE
15+ years of overall software development experience, with at least 10+ years experience specifically with data management systems and solutions.
8+ years of experience in banking or consumer lending credit risk management.
Experience leading projects involving data warehousing, data modeling, and data analysis
Design experience in Cloud Platforms like Azure Databricks, Google Cloud, Snowflake, Azure
Experience with business intelligence tools and technologies such as ETL, Power BI, and/or Tableau
Experience with database technologies such as SQL, NoSQL
Understanding of entity-relationship modeling, metadata systems, and data quality tools and techniques
Proficiency in the design and implementation of modern data architectures and concepts such as cloud services (AWS, Azure, GCP), real-time data distribution (Kafka, Dataflow), and modern data warehouse tools (Snowflake, Databricks)
Strong ability in programming languages such as Java, Python, and C/C++
Strong analytical and problem-solving skills
Ability in data science languages/tools such as SQL, R, SAS, or Excel
Ability to think strategically and relate architectural decisions and recommendations to business needs and client culture
Ability to assess traditional and modern data architecture components based on business needs
Ability to regularly learn and adopt new technology, especially in the ML/AI realm
Ability to synthesize and clearly communicate large volumes of complex information to senior management of various technical understandings
Ability to collaborate and excel in complex, cross-functional teams involving data scientists, business analysts, and stakeholders
Ability to guide solution design and architecture to meet business needs
Bachelor's Degree in Computer Science, Software Engineering, Information Systems or other related fields or equivalent work experience.

Company

Dataplatr Inc.

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Dataplatr specializes in data engineering & analytics with pre-built data models for Enterprise Applications like SAP, Oracle EBS, Workday, Salesforce to empower businesses to unlock the full potential of their data.
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