Data Engineering SMTS/LMTS- Revenue Analytics
InformaticaResponsibilities
- Lead the design, execution, optimization, and technical delivery of batch and event-driven data pipelines and scalable data products.
- Define data ingestion, transformation, orchestration, storage, data-contract, lineage, and reusable data-asset patterns using Python, SQL, dbt, Snowflake, and Airflow.
- Build and maintain Node.js services, middleware, and API integration components connecting data platforms with applications, dashboards, and enterprise systems.
- Implement agentic capabilities, AI-enabled workflows, autonomous-agent integrations, and Model Context Protocol server integrations.
- Establish testing, CI/CD, performance, observability, SLO, and SLA practices for data pipelines and application integration services.
- Conduct code and design reviews, mentor Senior and Associate Engineers, and champion clean code, automated testing, and documentation.
- Translate complex requirements into production-ready software and lead projects from requirements through deployment and ongoing operation.
Requirements
- Typically 10 to 14+ years of hands-on experience in Data Engineering, Software Engineering, or Platform Engineering, or equivalent demonstrated technical depth.
- Deep expertise in Python and advanced SQL, with extensive production data-platform experience.
- Strong experience with dbt, Apache Airflow, Apache Spark, and Snowflake, including optimization, tuning, cost management, and troubleshooting.
- Experience with distributed systems, dimensional or domain-oriented data modeling, batch and streaming patterns, and Data Mesh or data-as-a-product concepts.
- Practical experience with Node.js and TypeScript or JavaScript for backend services, microservices, or integration layers.
- Hands-on experience designing and consuming GraphQL, webhooks, and event queues such as Kafka and AWS SQS/SNS, plus knowledge of API gateways, OAuth2, and SSO.
- Experience building or integrating AI-enabled workflows with LangGraph or LangChain, MCP servers, structured outputs, context engineering, vector stores, and retrieval mechanisms.
- Experience using AI-native developer tools such as Cursor, Codex, or Claude Code with rigorous code review and testing.
- Hands-on AWS experience and familiarity with Docker, Kubernetes or ECS, Lambda, CI/CD pipelines, and Terraform.
- Proven ability to lead complex data projects, bridge data-platform and web-application teams, translate technical decisions into business outcomes, and communicate across engineering teams.
Benefits
- Salesforce provides benefits and resources intended to support balance and employee well-being.
- Salesforce offers reasonable accommodations during the application or recruiting process through its accommodations request process.
Tech Stack
Categories
About Informatica
Informatica (NYSE: INFA), a leader in AI-powered enterprise cloud data management, helps businesses unlock the full value of their data and AI. As data grows in complexity and volume, Informatica’s Intelligent Data Management Cloud™ delivers a complete, end-to-end platform with a suite of industry-leading, integrated solutions to connect, manage and unify data across any cloud, hybrid or multi-cloud environment. Powered by CLAIRE® AI, Informatica’s platform integrates natively with all major cloud providers, data warehouses and analytics tools— giving organizations the freedom of choice, avoiding vendor lock-in and delivering better ROI by enabling access to governed data, simplifying operations and scaling with confidence. Trusted by approximately 5,000 customers in nearly 100 countries—including over 80 of the Fortune 100—Informatica is the backbone of platform-agnostic, cloud data-driven transformation. Informatica. Where data and AI come to life.™ Contact: PR@informatica.com