Data Analyst

Salesforce is seeking a Data Analyst - Application Support Engineer to join the Corporate Strategy – Hyperscalers organization, supporting the build and evolution of our Estimation-as-a-Service (EaaS) platform. In this role, you will manage the full data lifecycle—from ingestion and cleaning to modeling and insights—ensuring the reliability, consistency, and business relevance of the data powering our estimation systems. You’ll collaborate with engineering, analytics, and product teams to connect data pipelines with estimation logic, support decision‑making, and drive continuous improvement through high‑quality, traceable data. If you enjoy bridging the gap between technical and business domains, designing data processes that scale, and shaping how data supports Salesforce’s consumption‑based strategy, this is the perfect opportunity. Responsibilities Design and maintain data pipelines and ETL processes to integrate, transform, and validate estimation and consumption data from multiple sources. Implement data cleaning, deduplication, and validation processes to ensure accuracy and reliability. Collaborate with engineering teams to align data models with API schemas and business entities (agents, topics, estimations, pricing, ROI). Work with product and analytics teams to define key metrics, business definitions, and reporting standards. Support the tracking and correlation of estimated vs. actual consumption, enabling continuous improvement of estimation models. Build dashboards and analytical views to provide visibility into system performance and business outcomes. Document data lineage, transformations, and ownership to strengthen governance and compliance. Contribute to the design of data retention, archival, and lifecycle management strategies. Partner with DevOps and Engineering to ensure observability, scalability, and security across the data stack. Qualifications 4+ years of experience in data engineering, analytics engineering, or data management roles. Solid understanding of relational databases (PostgreSQL, Snowflake, Redshift, or equivalent) and SQL proficiency for data manipulation and analysis. Experience building ETL/ELT pipelines using tools such as Airflow, Pentaho, dbt, or similar. Strong knowledge of data cleaning, validation, and transformation techniques. Familiarity with API‑based data flows, JSON structures, and integration with backend systems. Understanding of data governance, metadata management, and lifecycle controls. Strong analytical and problem‑solving skills, with attention to accuracy and traceability. Ability to communicate effectively with both technical and business stakeholders. Growth mindset and passion for learning new tools, frameworks, and data methodologies. Preferred Skills (Non‑Exclusive) Experience with Python or TypeScript for data processing and automation. Knowledge of data modeling methodologies (star/snowflake schemas, dimensional modeling). Familiarity with business intelligence tools (Tableau, Power BI, or Salesforce Analytics). Experience with version control (Git) and CI/CD for data workflows. Exposure to consumption‑based systems or product analytics. Awareness of cloud data ecosystems (AWS S3, Glue, Lambda, Athena). Success Indicators Reliable, automated data pipelines that ensure consistent, high‑quality inputs for estimation systems. Clear alignment between estimation data, consumption data, and business reporting. Improved visibility into estimation accuracy and customer consumption patterns. Documented data flows and lifecycle processes adopted across the team. Seniority Level Mid‑Senior level Employment Type Full‑time Job Function Information Technology Industry IT Services and IT Consulting #J-18808-Ljbffr