Data Management Operations (AWS/ Anlaytics/Python/AI)

The Opportunity

The Data Management Engineer is responsible for the administration, maintenance, and continuous improvement of the organization's big data Analytics environment. This role serves as a critical support function for the Analytics team, ensuring that platforms, tools, and cloud infrastructure operate reliably and efficiently. The ideal candidate is technically skilled, proactive, and eager to leverage emerging technologies — including artificial intelligence — to drive innovation within the Analytics ecosystem- Director,Data Management Operations

What You’ll Contribute

• Analytics Environment Management-The Data Management Engineer will manage and maintain the organization's big data Analytics environment, ensuring high availability, performance, and data integrity across all platforms. This includes monitoring system health, performing routine maintenance, coordinating upgrades, and troubleshooting issues as they arise. The Engineer will also develop and enforce data governance standards and best practices to support the reliability of the environment.
• Application and Tool Support-The Data Management Engineer will provide hands-on support for the applications and tools used by the Analytics team, including data ingestion pipelines, query engines, visualization platforms, and workflow orchestration tools. This includes onboarding new tools as business needs evolve, maintaining documentation, and serving as a technical resource for Analytics team members encountering platform-related issues.
• AWS EC2 Analytics Server Support-The Data Management Engineer will support and administer AWS EC2 instances that power the Analytics environment, including provisioning, configuration, scaling, performance tuning, and cost management. The role requires close collaboration with cloud and infrastructure teams to ensure that server resources align with Analytics workloads and organizational security requirements.
• AI Integration and Optimization-The Data Management Engineer will actively learn and apply artificial intelligence and machine learning tools to optimize and enhance the Analytics environment. This includes identifying opportunities to automate routine tasks, improve data processing efficiency, and integrate AI-driven capabilities into existing workflows. The Engineer is expected to stay current with developments in AI tooling relevant to data management and analytics infrastructure.

What We’re Seeking

• Should have a minimum of 6.5 years of experience in data engineering, analytics infrastructure, or a related field, along with a bachelor's degree in Computer Science, Information Systems, Data Engineering, or equivalent practical experience.
• Candidates should have demonstrated experience working with big data platforms such as Hadoop, Spark, and Hive, along with working knowledge of AWS services, particularly EC2, S3, EMR, and IAM.
• Familiarity with languages such as C, Java, Python, PySpark, HTML, JavaScript, jQuery, Scala, PERL, Bash, SQL, and PL/SQL is expected.
• Experience with AI or ML tools in a data engineering context is a plus, as is experience with infrastructure-as-code tools such as Terraform or CloudFormation and Apache HTTP server configuration and management.
• The right candidate is someone who takes ownership of the systems they manage, communicates clearly with both technical and non-technical stakeholders, and approaches problems with curiosity and a solutions-oriented mindset. A genuine interest in the evolving role of AI in data infrastructure will set strong candidates apart.

Our Offer to You

• An inclusive culture strongly reflecting our core values: Act Like an Owner, Delight Our Customers and Earn the Respect of Others.
• The opportunity to make an impact and develop professionally by leveraging your unique strengths and participating in valuable learning experiences.
• Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so.
• An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie.