Data Engineering & Analytics, Software Engineering MTS

About the Role

The Digital Enterprise Technology team is seeking a highly motivated Member of Technical Staff (MTS) – Data Engineering & Analytics to build scalable data solutions, develop impactful analytics, and drive data-informed decision-making across the organization. This role combines Data Engineering, Business Intelligence, and AI-driven analytics capabilities. The ideal candidate will have strong expertise in ETL development, Data Warehousing, Snowflake, Informatica, Tableau, and SQL, along with a passion for modern AI-powered and agentic technologies. You will be responsible for designing data pipelines, transforming complex datasets into meaningful insights, and creating intuitive dashboards that help business stakeholders make informed decisions.

Key Responsibilities

• Design, develop, and maintain scalable ETL pipelines using Informatica and modern data integration tools.

• Build and optimize data solutions on Snowflake and enterprise Data Warehouse platforms.

• Develop robust data transformation and data wrangling processes to support reporting and analytics requirements.

• Create visually compelling and actionable Tableau dashboards, reports, and stories that drive business insights.

• Partner with business stakeholders to understand reporting requirements and independently translate data into meaningful visualizations and analytics solutions.

• Write and optimize complex SQL queries to extract, transform, and analyze large datasets from multiple sources.

• Manage and support Tableau Server environments, including permissions, folder structures, schedules, subscriptions, and governance best practices.

• Ensure data quality, consistency, and reliability across reporting and analytics platforms.

• Collaborate with engineering, product, and business teams to establish scalable data models and reporting frameworks.

• Leverage AI-assisted development tools and explore agentic technologies to improve data engineering and analytics productivity.

• Contribute to AI-driven analytics initiatives, intelligent automation, and next-generation data solutions.

Required Qualifications & Experience

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related technical field.

• 4+ years of experience in Data Engineering, Business Intelligence, Data Warehousing, or Analytics Engineering.

• Strong hands-on experience with:

  • Informatica PowerCenter or equivalent ETL tools

  • Snowflake

  • Enterprise Data Warehousing concepts

  • Data Modeling and Data Transformation

• Advanced Tableau Desktop expertise, including:

  • Dashboard design and development

  • Advanced calculations

  • Parameters, LOD expressions, table calculations

  • Performance optimization

  • Latest Tableau features and capabilities

• Strong knowledge of Tableau Prep or equivalent data preparation and transformation tools.

• Experience administering Tableau Server, including:

  • Permissions and security models

  • Folder/project structures

  • Job scheduling

  • Dashboard subscriptions

  • Content governance

• Advanced SQL skills with the ability to:

  • Write complex custom SQL queries

  • Optimize query performance

  • Work with large-scale datasets

  • Develop reusable reporting datasets

• Ability to independently create dashboard and storytelling solutions without extensive wireframes or detailed guidance.

• Strong understanding of reporting, analytics, data visualization, and business intelligence best practices.

• Excellent analytical, problem-solving, and communication skills.

Preferred Skills & Qualifications

• Experience with CRM Analytics (Tableau CRM / Einstein Analytics).

• Experience with Salesforce data models and Salesforce platform reporting.

• Exposure to modern cloud data platforms and big data technologies.

• Experience using AI-powered development tools such as GitHub Copilot, Cursor, Claude Code, Gemini, or similar tools.

• Understanding of Agentforce, AI agents, workflow orchestration, and AI-driven SDLC practices.

• Experience applying AI techniques to data engineering, reporting, analytics, or operational automation.

• Familiarity with Agile development methodologies and DevOps practices.

• Experience building data products, executive dashboards, and enterprise-scale reporting solutions.

What Makes You Successful

• Strong ETL and Data Engineering foundation.

• Ability to convert complex datasets into compelling business insights.

• Passion for data visualization and storytelling.

• Curiosity to adopt AI-native engineering practices and agentic technologies.

• Ability to work independently, take ownership, and deliver high-quality analytics solutions with minimal supervision.