Data Engineer

Citizen Watch Company Of America, Inc.; New York (NY); On-site; USD 90,000 - 95,000; Full time

Job summary

The Data Engineer at Citizen Watch Company Of America, Inc. will collaborate with Data Scientists, Analysts, and business stakeholders to build scalable data solutions and operationalize AI applications.

Responsibilities include designing ETL/ELT pipelines, optimizing data warehouses and lakes, and deploying workloads on Snowflake, Databricks, and AWS, with Kubernetes-based orchestration and CI/CD practices to ensure reliability and security.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
• 1–3 years of experience in Data Engineering, DataOps, ML Ops, or a related role.
• Strong proficiency in Python.
• Strong experience with SQL and database optimization.
• Hands-on experience building and maintaining ETL/ELT pipelines.
• Experience with Snowflake, Databricks, or equivalent modern data platforms.
• Experience with AWS or similar cloud platforms.
• Experience with Kubernetes or equivalent container orchestration technologies.
• Understanding data warehousing, data lakes, and modern data architectures.
• Experience with Git and software development best practices.

Responsibilities

• 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.
• 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.

Skills

Python

SQL

ETL/ELT pipelines

Git

Data warehousing concepts

Education

Bachelor's degree in CS, Engineering, Information Systems, or related field

Tools

Snowflake

Databricks

AWS

Kubernetes

Airflow

Dagster

Prefect

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

• 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.
• 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.
• 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.

Required Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field.
• 1–3 years of experience in Data Engineering, DataOps, ML Ops, or a related role.
• Strong proficiency in Python.
• Strong experience with SQL and database optimization.
• Hands-on experience building and maintaining ETL/ELT pipelines.
• Experience with Snowflake, Databricks, or equivalent modern data platforms.
• Experience with AWS or similar cloud platforms.
• Experience with Kubernetes or equivalent container orchestration technologies.
• Understanding data warehousing, data lakes, and modern data architectures.
• Experience with Git and software development best practices.

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