Data & ML Engineer (Azure)

Robotics Technologies LLC
New York, NY, United States
3 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Compensation
$158,080
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Microsoft Azure Big Data Cloud Engineering Continuous Integration Information Engineering Extract Transform Load (ETL) DevOps Python (Programming Language) Machine Learning Performance Tuning Azure Data Lake
+20 more
SAP (Applications) SQL Databases Workflow Management Systems Parquet Data Logging Cloud Platform System Data Ingestion Azure Data Factory Cloud Monitoring Apache Spark Containerization Data Lakes Kubernetes Infrastructure Automation Frameworks Data Management Machine Learning Operations Azure Synapse Analytics Data Pipelines Docker Databricks

Job description

Seeking an experienced, hands-on Data & ML Engineer to support the design, development, and implementation of scalable data pipelines and machine learning solutions within an Azure cloud environment. The consultant will work collaboratively with internal engineering and data science teams to deliver reliable, secure, and production-ready solutions., * Design, develop, and maintain scalable data ingestion, transformation, and ETL/ELT pipelines.

  • Build and optimize Azure-based data platforms using Databricks, Data Lake, Synapse, and related technologies.
  • Support deployment and operationalization of machine learning models through CI/CD and MLOps practices.
  • Implement monitoring, logging, troubleshooting, and performance optimization for data and ML workloads.
  • Collaborate with data scientists and engineering teams to translate requirements into production-ready solutions.
  • Develop reusable, automated components following cloud engineering best practices.

Requirements

  • Proven hands-on experience as a Data Engineer, ML Engineer, or Cloud Platform Engineer.
  • Strong experience with Microsoft Azure data engineering services.
  • Proficiency in Python, SQL, and/or Scala.
  • Experience developing and supporting production-grade data pipelines.
  • Experience with Spark, Databricks, or comparable big data processing frameworks.
  • Familiarity with CI/CD pipelines, DevOps, and MLOps practices.
  • Ability to independently design, develop, troubleshoot, and deliver technical solutions.
  • Strong communication skills and experience working with cross-functional teams.

Preferred Qualifications:

  • Experience with Azure Data Factory, Synapse Analytics, and Azure Data Lake.
  • Experience with MLflow, Docker, Kubernetes/AKS, and containerized workloads.
  • Knowledge of Delta Lake, Parquet, and other common data formats.
  • Experience with infrastructure as code, orchestration tools, and cloud monitoring.
  • Exposure to enterprise data integrations, including SAP CDC.
  • Experience working in Agile development environments

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