Data and Machine Learning Engineer

As a Data and Machine Learning Engineer within the Data Engineering team, you will design, build, and optimize scalable data platforms and machine learning solutions in a Microsoft Azure environment. You will work with engineering and data science teams to deliver secure, reliable, production-ready capabilities.

Key Responsibilities

• Design, develop, and maintain scalable data ingestion, transformation, and ETL/ELT pipelines.
• Build and optimize Azure-based data platforms using Databricks, Synapse Analytics, Data Lake, and related cloud technologies.
• Deploy, operationalize, and support machine learning solutions through CI/CD pipelines and MLOps practices.
• Monitor, troubleshoot, and optimize data and machine learning workloads to support performance, reliability, and scalability.
• Collaborate with engineering and data science teams to translate business and technical requirements into production-ready solutions.

Required Qualifications

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

Technologies and Tools

• Microsoft Azure, Databricks, Synapse Analytics, Data Lake
• CI/CD, MLOps
• Python, SQL, Scala
• Apache Spark
• Azure Data Factory, Azure Data Lake
• MLflow
• Docker, Kubernetes, Azure Kubernetes Service (AKS)
• Delta Lake, Parquet
• Infrastructure as code, orchestration frameworks, cloud monitoring tools
• SAP Change Data Capture (CDC)

Helpful Background

• Experience with Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake.
• Knowledge of MLflow, Docker, Kubernetes, or Azure Kubernetes Service (AKS).
• Experience with Delta Lake, Parquet, and modern cloud data architectures.
• Familiarity with infrastructure as code, orchestration frameworks, and cloud monitoring tools.
• Exposure to enterprise data integrations, including SAP Change Data Capture (CDC).
• Experience working in Agile development environments.

Benefits

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Work Model and Location

This is an onsite position requiring 5 days a week in a client or Cognizant office in Mason, Ohio.

Salary, Incentives, and Application Deadline

• Applications will be accepted until November 08, 2026.
• Annual salary: $130,000 - $150,000 depending on experience and other qualifications.
• Eligible for Cognizant’s discretionary annual incentive program based on performance and subject to applicable plan terms.