Overview
Skills
Job Details
Our client, a major bank in New York City, is looking for Senior Data Architect (Director Level). 2/3 days on-site in NYC office.
This is a permanent FT career opportunity, Director - Level position with base salary range 220K-275K DOE, plus ~20-25% bonus and great benefits package.
Senior Data Architect
POSITION SUMMARY:
Seeking a highly experienced and innovative Senior Data Architect to join our Banking Technology team. This role is pivotal in designing, implementing, and managing data architecture solutions that support our Banking Division s data strategy. The ideal candidate will have a strong background in data architecture, data management, and financial services, with a focus on delivering high-quality, scalable, and secure data solutions in alignment with the firm s overall data effort.
Key Responsibilities Data Architecture Design
- Design and implement comprehensive data architecture solutions to support the Banking Division applications and processes.
- Develop and maintain data models, schemas, and metadata to ensure data consistency and quality across the organization.
- Collaborate with business stakeholders, Chief Data Office to understand data requirements and translate them into effective data architecture designs.
- Ensure data architecture aligns with industry best practices, regulatory requirements, and the organization's data governance policies.
Data Management
- Oversee data integration, data warehousing, and data lakes to support advanced analytics and reporting needs.
- Implement data quality and data cleansing processes to ensure the accuracy and reliability of data.
- Establish and enforce data management policies and procedures to enhance data security, availability, and integrity.
- Monitor and optimize database performance, ensuring efficient data retrieval and storage.
Technical Leadership
- Provide technical leadership and guidance to data engineers, developers, and analysts in designing and implementing data solutions.
- Stay current with emerging technologies and industry trends in data architecture and data management.
- Lead and participate in code reviews, design reviews, and architectural discussions to ensure high standards of data solution delivery.
- Mentor junior team members and foster a culture of continuous learning and improvement.
Qualifications
Educational Background
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, or a related field.
- Relevant certifications in data architecture, data management, or related technologies are a plus.
Professional Experience
- At least 10 years of experience in data architecture, data management, or related roles within the financial services industry, preferably in investment banking.
- Proven experience in designing and implementing data architecture solutions for complex financial systems.
- Strong understanding of data modeling, data integration, and ETL processes.
- Experience with database technologies such as SQL Server, Oracle, MySQL, PostgreSQL, and NoSQL databases like MongoDB and Cassandra.
- Familiarity with big data technologies such as Hadoop, Spark, and Kafka.
- Proficiency in programming languages such as Python, Java, or Scala.
- Experience with cloud platforms such as AWS, Azure, or Snowflake is highly desirable.
Skills and Competencies
- Strong analytical and problem-solving skills with the ability to work in a fast-paced, dynamic environment.
- Excellent communication and interpersonal skills to effectively collaborate with cross-functional technology & business teams and senior stakeholders.
- Ability to manage multiple projects and priorities simultaneously.
- Detail-oriented with a strong commitment to data quality and accuracy.
- Leadership skills with the ability to drive delivery and inspire and motivate team members.
Please email your resume or use this link to apply directly:
brainsworkgroup.catsone .com/careers/index.php?m=portal&a=details&jobOrderID=16655287
Or email: igork@brainsworkgroup .com
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Keywords: data architect java scala python sql mongodb snowflake etl oracle cassandra aws azure bank hadoop spark kafka