Senior Data Platform Engineer

Description

HiredScore is the leading provider of Talent Orchestration technology. HiredScore’s artificial intelligence, automation, and deep integrations empower the largest and most innovative companies in the world to safely and transparently drive critical business outcomes in recruitment productivity, diversity hiring, internal mobility, and total talent management.

HiredScore’s proprietary technology provides compliant-by-design AI that seamlessly connects to data and systems to power the shift to proactive and fair HR decisions. HiredScore is live in 150 countries and available in 70 languages.

As a Senior Data Platform Engineer, you will join the platform team that owns and manages the data source of truth in Hiredscore as well as the data platform and data pipelines.

Roles & Responsibilities

• Designing, building, profiling, and documenting our datasets and the ELT/ETL pipelines that build them.
• Creating and implementing architecture and standards for all data needs in the company
• Promoting and building AI solutions on top of data such as LLM analytics and automation by Gen AI
• Advocate for modern solutions and standards for data access, storage, and transformation across the Data and Engineering groups.
• Manage the integrity and performance of Hiredscore’s databases - MongoDB, Postgres, and Elasticsearch.
  
  

• 5+ years of experience in a similar role.
• Experience with Python.
• Hands-on with Big Data and Data Pipeline tech (Airflow, Spark, Kafka, etc.).
• Data and data platform enthusiast
• Proven commercial experience in designing and building data platforms/data pipelines/analytics platform
• Experience with 24/7 production databases
• Loves dashboards and observability
• Deep diver - not afraid to open dashboards, logs, K8S resources, and SSH into container in order to solve an issue
• Flourish in a team setting and able to mentor team members
• Technical thought leader who likes to push for high-value initiatives and raise the quality bar
  
  

• Experience working with Celery, RabbitMQ, Spark, BigQuery, IceBerg, MongoDB, PostgreSQL, Elastic