Senior Data Engineer

About the product

Responsibilities

• As a Senior Data Engineer, you will help implement scale our data infrastructure to support product features, AI/ML workflows, and analytics and business intelligence systems critical to our decision making and success. Specific responsibilities include:
• Design, implement, and maintain high volume data pipelines across the application stack
• Manage and scale relational, document and search data stores to support rapid growth.
• Support streaming data and event-based data pipelines.
• Manage and create feature stores that enable rapid ML experimentation and deployment
• Support machine learning workflows, including feature engineering, model training pipelines, and model deployment.
• Implement ML Ops practices such as model versioning, monitoring, retraining, and CI/CD for ML models.
• Build and maintain business intelligence dashboards and data pipelines for both internal use and for our organization customers.
• Ensure best practices for data governance, quality, and security.

Requirements

• As a member of the Unified team, you can expect to engage with a set of individuals who are incredibly committed to their company’s mission. All Unified team members fundamentally believe in the potential impact of our work on society. That means we expect a lot from each other and those we work with. In practice, this means we look for the following attributes in all of our employees:
• Defaults to action in everything they do
• Very organized and highly effective in terms of time management
• Extreme attention to detail
• Highly responsive to other team members’ requests
• Takes time to learn new tools or best practices when necessary
• Listens to others and seeks out feedback from team members and third parties
• Is very engaged in understanding the organizations and individuals whom we serve
• Specific technical skills that will be helpful in this role include:
• Programming Languages : Proficiency in Python (including Pandas, Polars) and SQL; familiarity with JavaScript preferred.
• Datastores : Experience optimizing document and relational datastores. PostgreSQL required. MongoDB, Redis and Elasticsearch are a plus.
• Data Warehouse: Familiarity with BigQuery, Redshift or Snowflake or similar as well as data processing frameworks such as Spark and Scala
• Workflow Orchestration : Hands-on experience with Apache Airflow, Kafka, AWS Lambda, GCP Cloud Functions, Prefect, Temporal, or similar scheduling/pub-sub/orchestration tools.
• ML Ops : Familiarity with tools/frameworks for machine learning pipelines (e.g., Ray, MLflow, SageMaker, Vertex AI).
• Infrastructure : Experience with distributed systems, including Docker and Kubernetes for containerization and deployment.

What this role offers

How to apply

• Submit your information here: https://airtable.com/appvg1UAQgKCzR0Xl/pagj1kyfmXMRJ1mJA/form
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