Data Engineer

Digitailor; New York (NY); On-site; USD 90,000 - 95,000; Full time

Job summary

Digitailor is hiring a Data Engineer in New York, NY. You will design and maintain scalable data pipelines and data models, ensuring data quality and governance across production systems. Collaborate with data scientists and analysts to operationalize AI/ML solutions on cloud platforms.

The role emphasizes deploying AI/ML applications, maintaining observability, and integrating MLOps tools to support reliable, scalable data workflows in a fast-paced environment.

Qualifications

• Experience deploying and supporting AI/ML applications in production.
• Experience with ML lifecycle tools and orchestration frameworks.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines and data models.
• Build and optimize data warehouses and data lakes.
• Develop automated data ingestion, transformation, and orchestration workflows.
• Manage and optimize data platforms such as Snowflake, Databricks, or equivalent.

Skills

ETL/ELT pipelines

Data modeling

Cloud platforms

Kubernetes

ML/AI deployment

Docker

CI/CD

Terraform/IaC

Airflow/Dagster/Prefect

MLflow/SageMaker/Kubeflow

Tools

Snowflake

Databricks

SageMaker

Kubeflow

Airflow

Dagster

Prefect

Docker

Terraform

CloudFormation

Prometheus

Grafana

CloudWatch

Datadog

Kafka

Job description

The Data Engineer works closely with Data Scientists, Data Analysts, and Business stakeholders to develop reliable data solutions and operationalize machine learning and AI applications.

Key Responsibilities

Data Engineering Design, develop, and maintain scalable ETL/ELT pipelines for structured and semi-structured data. Build and optimize data warehouses, data lakes, and data models. Develop automated data ingestion, transformation, and orchestration workflows. Manage and optimize data platforms such as Snowflake, Databricks, or equivalent . Ensure data quality, reliability, governance, and observability across data pipelines. Cloud & Platform Engineering Deploy and manage data workloads on AWS or similar cloud platforms (Azure/GCP) . Implement infrastructure and application deployments using containerized environments. Support and maintain Kubernetes-based deployments and related cloud services. Monitor platform performance and troubleshoot production issues. AI/ML Operations Support deployment, monitoring, and maintenance of AI/ML applications and services in production environments. Collaborate with Data Scientists to operationalize machine learning models and AI solutions. Implement basic MLOps practices using tools such as MLflow, SageMaker, Kubeflow, or equivalent platforms . Monitor AI application health, data drift, model performance, and system reliability. Collaboration & Continuous Improvement Work closely with cross-functional teams to gather requirements and deliver scalable solutions. Participate in code reviews, documentation, testing, and CI/CD processes. Continuously improve platform reliability, security, and operational efficiency.

Preferred Qualifications

Experience deploying and supporting AI/ML applications in production . Familiarity with LLM/Generative AI application deployment , inference endpoints, or AI service integration. Experience with ML lifecycle tools such as MLflow, Kubeflow, SageMaker, or Databricks ML . Experience with orchestration tools such as Airflow, Dagster, or Prefect . Knowledge of Docker and containerized application deployment. Familiarity with CI/CD pipelines and Infrastructure as Code (Terraform, CloudFormation). Exposure to monitoring tools such as Prometheus, Grafana, CloudWatch, or Datadog. Experience with streaming technologies such as Kafka is a plus. EEOE Annual Salary range: $90,000.00 - $95,000.00