Salesforce Data Engineer

Role Summary

We are seeking a highly skilled Salesforce Data Engineer responsible for designing, building, and optimizing scalable data pipelines and data integration solutions across the Salesforce ecosystem and external platforms.

This role focuses on enabling reliable data movement, analytics, and AI-driven capabilities while ensuring governance, security, and performance.

This role will focus on modernizing legacy Informatica pipelines into Azure-native architectures while enabling robust, scalable, and performant data integration with Salesforce and enterprise systems. The Salesforce Data Engineer partners closely with Salesforce Developers, Agentforce Engineers, Architects, and DevOps teams to deliver secure, high‑quality, and performant data foundations that power intelligent automation and business decision‑making.

Duties & Responsibilities

· Design, build, and modernize scalable, high-performance ETL/ELT pipelines and data integration solutions across cloud and enterprise platforms

· Translate complex business requirements into optimized, scalable data transformation, integration, and data flow architectures

· Develop and maintain robust integrations between Salesforce and enterprise systems, ensuring reliable and secure data exchange

· Lead the migration of legacy Informatica workflows to Azure Data Factory (ADF) and cloud-native architectures, applying modern design patterns and best practices

· Develop and optimize advanced SQL transformations across Oracle, Snowflake, and MySQL, ensuring performance, scalability, and cost efficiency

· Drive ETL/ELT performance optimization through query tuning, execution plan analysis, workload management, and pipeline optimization

· Design and implement scalable data models and data warehouse solutions, ensuring strong data lineage, traceability, and reusability

· Establish and enforce data quality frameworks, validation rules, and governance standards across data pipelines and integrations

· Enable modern data architecture patterns, including zero-copy, federated data access, and near real-time data integration

· Own production operations, including monitoring, incident management, root cause analysis, and SLA-driven support for critical data pipelines

· Automate orchestration, scheduling, monitoring, and documentation to improve reliability, observability, and operational efficiency

· Collaborate cross-functionally with Salesforce Developers, Agentforce Engineers, Architects, and business stakeholders to align data models with application, automation, and AI/agent use cases

· Partner with architecture teams to define scalable data architecture patterns, canonical models, and governance strategies within the Salesforce and enterprise data ecosystem

· Create and maintain comprehensive documentation for data pipelines, transformations, mappings, workflows, and operational processes

Minimum Years of Experience

4–6 years of experience in data engineering, analytics engineering, or platform data integration.

4+ years of hands‑on experience with Informatica Power Center

2+ years of hands-on experience with Python

Basic Qualifications

· Bachelor's degree in computer science, Information Technology, Engineering, or a related field

· 5+ years of experience in data engineering and ETL/ELT development

· Strong hands-on expertise in Informatica PowerCenter and Azure Data Factory (ADF)

· Advanced SQL development skills across Oracle, Snowflake, and MySQL

· Proven experience in ETL/ELT design, development, and performance optimization, including query tuning and pipeline efficiency

· Experience integrating Salesforce with enterprise systems, ensuring reliable and scalable data exchange

· Solid understanding of data warehousing concepts, data modeling, ETL design patterns, and end-to-end data lineage

· Experience with production support, including incident management, root cause analysis, and resolution

· Hands-on experience with scheduling and orchestration tools (e.g., Tidal or similar platforms)

· Familiarity with modern data architecture patterns, including zero-copy and federated data access

· Experience working in Agile/Scrum environments, with strong collaboration across cross-functional teams

· Strong analytical and problem-solving skills, with the ability to troubleshoot complex data issues

Preferred Qualifications

· Salesforce platform familiarity or relevant certifications (e.g., Data Cloud, Platform, Integration)

· Exposure to modern cloud data architectures, particularly within the Azure ecosystem

· Working knowledge of advanced Snowflake capabilities, such as data sharing, clustering, and performance optimization

· Experience leading or contributing to ETL/ELT migrations from legacy platforms to cloud-native solutions

· Strong understanding of data governance, data quality frameworks, and compliance best practices

· Ability to effectively collaborate in complex, cross-functional enterprise environments with multiple stakeholders · Experience using Python for data engineering, automation, or pipeline development

· Familiarity with Databricks or other advanced analytics and data processing platforms