Database Engineer

Company Description

Kaufman & Ungar Finance Solutions is redefining the landscape of financial services by expanding into diverse sectors to meet the evolving needs of their global clientele. They offer expert business plan development, high-performance client portfolio management, innovative blockchain and cryptocurrency solutions, community-focused infrastructure development, strategic real estate investments, and cutting-edge programming and software development services. The company is dedicated to delivering exceptional value and fostering positive change through their commitment to charitable initiatives.

We are seeking a highly skilled Database Engineer to join our team and tackle challenging data problems with creativity and efficiency. The ideal candidate will be responsible for designing, maintaining, and optimizing complex databases, with a focus on writing advanced queries and implementing algorithmic solutions for large-scale data manipulation. You will collaborate closely with other teams to ensure seamless data integration, performance, and scalability.

1. Design and Development:

• Design and implement robust database structures that support complex queries and efficient data processing.
• Create and maintain relational and/or NoSQL database models tailored to business requirements.

Advanced Querying:

• Write, optimize, and maintain advanced SQL queries, including nested and recursive queries, complex joins, and window functions.
• Develop stored procedures, triggers, and scripts to automate repetitive tasks and enhance functionality.

Performance Optimization:

• Analyze and optimize slow queries, indexes, and database structures for maximum performance.
• Perform load testing and capacity planning for large-scale data environments.

Algorithmic Problem Solving:

• Develop and implement algorithms to solve complex data processing challenges.
• Work with large datasets and ensure data integrity, accuracy, and consistency.

Integration and Maintenance:

• Collaborate with development teams to integrate databases into applications and data pipelines.
• Monitor database health, resolve issues, and maintain backups and disaster recovery solutions.

ETL Processes (if applicable):

• Design and implement ETL workflows for data extraction, transformation, and loading.

Documentation and Reporting:

• Document database architecture, schemas, and processes.
• Provide technical reports and visualizations as needed.

Technical Skills:

• Expert-level proficiency in SQL and query optimization techniques.
• Experience with database systems such as MySQL, PostgreSQL, Oracle, or SQL Server.
• Knowledge of NoSQL databases (e.g., MongoDB, Cassandra) is a plus.
• Proficiency in at least one programming language (Python, Java, etc.) for data manipulation and automation.

Problem-Solving:

• Strong algorithmic thinking and ability to solve complex data challenges.
• Familiarity with data structures and algorithms in the context of databases.

Performance and Scalability:

• Proven experience in optimizing database performance and handling large-scale datasets.
• Knowledge of indexing, partitioning, and caching strategies.

Analytical and Communication Skills:

• Strong analytical mindset and attention to detail.
• Ability to communicate technical concepts effectively to non-technical stakeholders.

Preferred Experience:

• Hands-on experience with ETL tools and data integration frameworks.
• Familiarity with cloud database services (AWS RDS, Google Cloud SQL, etc.).
• Exposure to big data technologies (Hadoop, Spark, Hive) is a plus.

• A challenging, data-driven environment where innovation and efficiency are encouraged.
• Opportunities to work on complex, impactful projects that make a difference.
• A collaborative team culture with room for growth and learning.