HOW YOU WILL MAKE HISTORY HERE...As a Senior Analyst - Application Operations, you will be a hands-on member of the Data Analytics and AI Operations team, responsible for operating, monitoring, troubleshooting, and continuously improving enterprise data and analytics platforms.
You will bring strong Data Engineering and Data Analytics experience to ensure reliable data pipelines, high-quality data, actionable insights, and trusted analytics. You will leverage industry-leading technologies including Databricks, Snowflake, Azure Data Factory (ADF), Informatica, Python, SQL, MicroStrategy and Power BI to deliver scalable, secure, and high-performing data solutions. Your work will help drive digital transformation, enable AI innovation, and ensure trusted data is available to stakeholders across the enterprise. You will also apply working knowledge of AI and Machine Learning to support evolving data, analytics, and AI capabilities. The technologies and responsibilities listed below are not limited to those specifically identified.
WHAT YOU WILL DO...- Perform hands-on Data Engineering and Data Analytics across enterprise data platforms and solutions.
- Build, monitor, troubleshoot, and optimize ETL/ELT pipelines, workflows, integrations, and data jobs.
- Perform hands-on SQL and Python data analysis, validation, reconciliation, profiling, and root cause analysis.
- Support the data pipelines across SAP S/4HANA, SAP Datasphere, SAP SLT, ERP, APIs, cloud applications, and other enterprise systems.
- Analyze and resolve data quality, pipeline, performance, and integration issues.
- Develop and support Power BI, MicroStrategy, reports, dashboards, KPIs, metrics, and operational analytics.
- Create and maintain trusted data products, curated datasets, and semantic layers that support enterprise analytics and AI use cases.
- Support and maintain curated datasets, semantic layers, data models, and enterprise reporting.
- Support data administration activities, including access, permissions, user management, job scheduling, environment support, monitoring, and data platform operations.
- Develop Python/SQL automation to improve efficiency and reduce manual effort.
- Monitor data and platform performance and proactively identify operational risks.
- Lead incident investigation, troubleshooting, resolution, and corrective actions.
- Maintain runbooks, SOPs, monitoring standards, and technical documentation.
- Drive data quality, governance, security, lineage, metadata, and compliance practices.
- Identify opportunities for automation, optimization, reliability, and continuous improvement.
- Apply knowledge of AI/ML concepts and data requirements to support emerging analytics and AI initiatives.
- Serve as a hands-on technical resource for data and analytics issues.
WHO YOU WILL WORK WITH...- Data Engineering teams supporting enterprise data platforms, pipelines, integrations, and data products.
- Analytics and BI teams supporting Power BI, MicroStrategy, reporting, dashboards, and analytics solutions.
- Platform Engineering and Cloud teams supporting Databricks, Snowflake, Azure, monitoring, and reliability.
- Data Science and AI Engineering teams supporting AI, ML, and advanced analytics initiatives.
- Business Owners and Product Owners to align data solutions with business priorities and outcomes.
- Digital Partners and Digital Product teams supporting digital solutions, data products, and integrations.
- Data Governance, Security, and Compliance teams supporting data quality, standards, lineage, and controls.
- Data Architects and Enterprise Architecture teams supporting data strategy and modernization.
- Business stakeholders across Supply Chain, Finance, Sales, Marketing, and Corporate Functions.
WHAT YOU BRING TO THE TABLE... (MUST HAVE)- Bachelor's degree in Computer Science, Information Systems, Data Engineering, Business Analytics, or a related technical field.
- 5+ years of hands-on experience across both Data Engineering and Data Analytics.
- Strong hands-on SQL skills for data analysis, troubleshooting, validation, reconciliation, and root cause analysis.
- Hands-on experience building, monitoring, troubleshooting, and optimizing ETL/ELT pipelines Databricks and Snowflake
- Strong experience with Databricks and/or Snowflake, or similar enterprise data platforms.
- Experience with ADF, Informatica, ADLS, or similar cloud data technologies.
- Hands-on Python experience for data analysis, automation, and operational solutions.
- Hands-on experience with Power BI, MicroStrategy, or similar analytics and reporting platforms.
- Strong understanding of data modeling, data quality, data governance, data lineage, metadata, and data security.
- Experience with production support, incident management, monitoring, and problem resolution.
- Strong troubleshooting, analytical, and problem-solving skills, with the ability to drive issues through resolution.
- Working knowledge of AI and Machine Learning concepts, including common AI/ML use cases, data requirements, and the ML lifecycle.
- Strong communication and stakeholder-management skills across technical and business teams.
- Ability to work independently, take ownership, prioritize effectively, and deliver hands-on solutions.
- Demonstrated ability to drive automation, reliability, efficiency, and continuous improvement.
IT WOULD BE GREAT IF YOU HAVE... (NICE TO HAVE)- Experience in MLOps, AI Operations, Generative AI, or Agentic AI to enable Machine Learning, Generative AI, and Agentic AI initiatives through scalable, governed, and high-quality data solutions.
- Knowledge of feature engineering, model monitoring, ML/AI pipelines, or AI platforms.
- Knowledge of SAP S/4HANA, SAP Datasphere, SAP SLT, and SAP data integration.
- Experience in Unity Catalog, data catalogs, lineage, and metadata management.
- Experience in data and platform observability tools.
- Certifications in Databricks, Snowflake, Azure, Informatica, Generative AI, or Agentic AI or related is preferred.
PREFERRED TECHNICAL SKILLSData Engineering: Databricks • Snowflake • PySpark • Python • SQL • ADF • Informatica • ADLS • ETL/ELT • Data Modeling
Data Analytics & Operations: Data Analytics • Data Operations • Power BI • MicroStrategy • Reporting • Dashboards • KPIs • Production Support • Monitoring • Incident Management • Root Cause Analysis
Data Governance & Quality: Data Quality • Data Validation • Data Reconciliation • Data Profiling • Data Governance • Data Lineage • Metadata • Data Security
Data Administration Knowledge: Platform Administration • Access & Permissions • User Management • Job Scheduling • Environment Management • Data Monitoring
Automation: Python/SQL Automation • Git • CI/CD • DevOps
AI & ML Knowledge: AI/ML Fundamentals • ML Lifecycle • Feature Engineering • Model Monitoring • Generative AI • MLOps
Compensation and Benefits:The target base salary range for this full-time, salaried position is between
$101,100-$139,000
Individual base pay depends on work location and additional factors such as experience, job-related skills, and relevant education or training. Total pay may include other forms of compensation. In addition, we offer competitive health, dental, 401k and wellness benefits beginning on the first day of employment. Please ask your Talent Acquisition Partner for more information about our total rewards package.
