Role Name: EDM/MTC - DataOps Engineer
Location: FL (Hybrid
Duration: 12 month
We are looking for an experienced DataOps Engineer to build, automate, and maintain scalable data pipelines and data infrastructure. The ideal candidate should have strong experience in data engineering, CI/CD, workflow orchestration, cloud platforms, and data pipeline monitoring.
Design, develop, and maintain automated data pipelines and workflows.
Implement DataOps practices to improve data delivery, quality, reliability, and performance.
Build and manage CI/CD pipelines for data engineering processes.
Automate data integration, testing, deployment, and monitoring.
Work with data engineers and analytics teams to ensure reliable data operations.
Monitor pipeline performance, troubleshoot failures, and perform root-cause analysis.
Implement data quality checks, validation, and governance processes.
Manage workflow orchestration and scheduling.
Optimize data pipeline performance and cloud infrastructure costs.
5+ years of experience in Data Engineering, DataOps, or related roles.
Strong programming skills in Python and SQL.
Experience with ETL/ELT pipelines and data integration.
Hands-on experience with Apache Airflow or similar orchestration tools.
Experience with CI/CD tools such as Jenkins, GitLab CI, or Azure DevOps.
Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform.
Experience with data warehouses and data platforms such as Snowflake, Databricks, BigQuery, or Redshift.
Knowledge of Docker, Kubernetes, Git, and Infrastructure as Code (Terraform).
Experience with data monitoring, logging, testing, and troubleshooting.
Experience with Apache Spark, Kafka, and distributed data processing.
Knowledge of data quality tools such as Great Expectations or dbt tests.
Experience implementing DataOps automation and observability frameworks.
Understanding of DevOps, MLOps, and data governance practices.
A hands-on DataOps Engineer with strong Python, SQL, pipeline automation, CI/CD, cloud, and orchestration experience who can ensure reliable, scalable, and efficient data operations.
