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Database Platform Engineer

2 months ago

New York, United States New York Technology Partners Full time

Job title: Database Platform Engineer

Location: New York, NY

Position: Permanent/ Fulltime


Job Description:

  • Client is looking for an innovative, driven self-starter engineer to join the Database Platform Team with a strong focus on automation and a broad knowledge of database technologies.
  • The ideal candidate will have extensive experience with databases such as PostgreSQL and MongoDB as well as AWS managed database offerings.
  • Operational knowledge in Linux and Python programming is also essential.
  • The role involves designing, implementing, and managing database solutions that support our organization’s data management needs while ensuring high availability, performance and security as well as having a heavy focus on coding and automation.
  • The candidate will embody a mindset of continuous learning and process improvement.


As a Database Platform Engineer will be involved in:

  • Design, implement, and manage database solutions across a variety of platforms including PostgreSQL, Snowflake, ClickHouse, SQL Server, Aurora, RDS, DynamoDB, and MongoDB.
  • Develop the golden build for all PostgreSQL, ClickHouse, MongoDB, RDS, and Aurora installations, setting the standard for database excellence within the organization.
  • PostgreSQL administration SME with 5+ years of experience managing PostgreSQL databases on-premise and on AWS.
  • Develop and maintain automation scripts and tools to streamline database operations and processes.
  • Ensure database systems operate efficiently, with high availability and performance.
  • Implement and manage database security measures, including access controls and encryption.
  • Collaborate with development teams to optimize database structures, queries, and indexes.
  • Conduct regular database maintenance tasks, including backups, restores, and performance tuning.
  • Monitor database systems to identify and resolve issues proactively.


To be considered a good cultural fit, you must be:

  • An ambitious self-starter, hungry and driven to learn.
  • A very strong and efficient communicator and collaborator.
  • Able to multi-task and excel in a high-pressure, fast-paced trading environment.
  • Work well under minimal supervision to complete projects and tasks on time.
  • Able to think on your own to develop quick and sound solutions to complex problems.
  • Strong desire to solve with automation and self-service.
  • Willingness to participate in on-call rotation during off hours and weekends. Initially one week every five (will vary based on team size).
  • Stay up to date with emerging database and automation technologies, trends, and evaluate their applicability to our environment.
  • Quick learner.


To be considered a good technical fit, you must have:

  • A minimum of 7 years of hands-on experience managing medium/large enterprise database platforms
  • Expert knowledge of PostgreSQL features, functionality and optimization techniques including RDS and Aurora flavors
  • Strong knowledge of at least at least one of MongoDB, DynamoDB, Redshift and Snowflake
  • Operational Knowledge of SQL Server
  • Strong knowledge of data modelling across different database systems
  • Strong knowledge of Linux
  • Experience using Python for automation tasks
  • Experience with Infrastructure as Code tools, such as Terraform and Cloud Formation
  • Experience running applications and databases in containers (Docker, Kubernetes)
  • Experience with CI/CD platforms and automation of SDLC processes
  • Experience in declarative automation tools such as Puppet and Ansible


Bonus points for:

  • Knowledge of reporting solutions such as PowerBI or Tableau
  • Experience managing OLAP database engines like ClickHouse, Druid or Apache Pinot
  • Practical experience in the deployment and management of Apache Zookeeper or similar distributed coordinators
  • Strong scripting knowledge of Powershell and Powershell Core
  • Proficiency in orchestrating and scheduling complex dataflows using Apache Airflow