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À propos
What You’ll Do
Architect Multi-Stage Medallion Pipelines: Design and oversee the implementation of a robust Medallion Architecture (Bronze, Silver, and Gold layers), ensuring seamless transitions from raw ingestion to highly refined, business-logic-heavy data assets.
Lead Semantic Layer Strategy: Own the development and governance of the Semantic Layer, defining standardized metrics and dimensions to ensure consistent interpretation of KPIs across all downstream business intelligence and reporting platforms.
Advanced Dimensional Modeling: Lead the transition from flat tables to sophisticated Star and Snowflake schemas. Design high-performance data models that support complex relationship mapping, historical versioning (SCD Type 2), and high-concurrency querying.
Engineering Identity & Entity Resolution: Build and maintain scalable pipelines for identity resolution, stitching together disparate data points across the Salesforce ecosystem to create unified, governed customer and product graphs.
Infrastructure for Causal & Attribution Modeling: Partner with Decision Scientists to engineer the specialized data structures and features required for advanced attribution and causal inference, ensuring these models are backed by high-integrity, production-ready data.
Data Contracts & Quality Governance: Establish and enforce strict Data Contracts between upstream producers and downstream consumers. Implement automated validation frameworks to monitor data freshness, schema drift, and semantic accuracy.
Operational Excellence & CI/CD: Drive engineering best practices by implementing rigorous CI/CD workflows for data pipelines, emphasizing automated testing, version control for SQL/Python transformations, and proactive performance tuning.
Cross-Functional System Design: Collaborate with Product Managers and Engineering leaders to translate complex business requirements into scalable technical architectures, prioritizing data lineage, transparency, and low-latency access to trusted metrics.
Qualifications
8+ years of experience as a Data Engineer or in a similar role.
A related technical degree required.
Proficiency in data engineering tools and languages, such as Python, SQL, and Spark.
Strong understanding of database concepts, data modeling, and ETL processes with tools like Airflow, dbt, Informatica, etc.
Experience with cloud-based data solutions (e.g., AWS, Azure, Google Cloud).
Familiarity with data warehousing, SQL, NoSQL databases, and data integration techniques.
Experience with the Salesforce Ecosystem, specifically Data Cloud.
Problem-solving skills to troubleshoot and resolve data-related issues.
Excellent communication skills and ability to collaborate in a cross-functional environment.
The typical base salary range for this position is $172,500 - $260,100 annually.
Benefits include time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program.
Posting Statement Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. All employees or potential employees are assessed on the basis of merit, competence and qualifications without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, and assessment of job performance, discipline, termination and all related activities. Recruiting, hiring, and promotion decisions are based on merit and the same goes for compensation, benefits, and transfers. This policy also applies to the entire employment journey at Salesforce.
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Compétences linguistiques
- English
Avis aux utilisateurs
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