Senior Manager, Data Management and Operations

Candidates must be willing to participate in at least one in-person interview .

Managing and scaling distributed data architectures while maintaining cloud cost-efficiency represents a major modern operational challenge. This role directly addresses these complexities by leading the development, deployment, and optimization of robust cloud data platforms. By directing collaborative, cross-functional engineering teams across both on-site and offshore locations, the manager ensures stable real-time data flow and rapid issue resolution.

This position is central to transforming raw business requirements into performant, automated data integration pipelines.

- Lead the operations and delivery of big data solutions using modern cloud data platforms - Manage day-to-day development activities for new data solutions and troubleshoot existing production implementations - Coordinate with product owners and technical leads to resolve architectural and integration issues - Optimize AWS and data warehouse configurations to improve performance and reduce operational cloud spend - Design and implement automated CI/CD pipelines to streamline code deployments and pipeline reliability - Integrate AI-driven operations tools to automate anomaly detection and predictive data quality checks

- Critical experience designing and building large-scale distributed big data pipelines - Proven leadership managing and coordinating multi-site and offshore production support operations - Strong technical capability in developing ingestion and curation pipelines using Databricks - Proficiency in software engineering principles using Spark, Python, or Scala - Deep understanding of database management systems, version control, and CI/CD concepts - Practical AI application skills to automate and optimize data management tasks

- Experience with change data capture tools such as Qlik or Goldengate - Familiarity with scheduling tools such as Control-M, Airflow, or AWS Step Functions - Knowledge of Infrastructure-as-Code using Terraform or AWS CloudFormation

- Minimum Education: Bachelor's Degree in Computer Science, Information Technology, or a related field - Minimum Experience: 5 years of experience in distributed data engineering; 3 years of experience leading on-site or offshore teams - Required Technical Skills: Must have at least 2 years of experience with:

- AWS cloud infrastructure optimization - Spark, Python, or Scala programming - Kafka, Apache Flink, or real-time streaming tools - Git and GitLab version control pipelines