Salesforce Data Engineer

What You'll Do:We are seeking a highly skilled Data Engineer to join our innovative Digital Integration & Optimization team comprised of passionate data professionals who combine a diverse range of knowledge, skills, experience, and expertise to deliver world class solutions enabling a data driven organization.

The ideal candidate for this role will have extensive experience collaborating with cross-functional teams to deliver, monitor, and maintain high-quality data workflows. You will play a key role in constructing, testing, monitoring, maintaining, and enhancing critical data pipelines between multiple databases and business systems vital to our marketing, sales, and customer support teams.

Responsibilities

• Contribute to data profiling initiatives across core RevOps and go-to-market (GTM) systems to evaluate data quality, consistency, and completeness.

• Construct, deploy, and maintain scalable data workflows spanning Salesforce, Siebel CRM, Oracle ERP, SQL Server, and Azure Cloud data sources.

• Engineer, support, and enhance robust data pipelines and automated transformation processes using SQL and big data technologies (e.g., Python, Hadoop, Spark).

• Develop and implement database scripts, triggers, functions, and stored procedures.

• Develop automated testing and validation procedures to enhance data quality management and compliance with data governance policies.

• Participate with cross-functional teams across the organization to understand data needs within stakeholder contexts and how technical decisions impact analytics and reporting needs.

• Work collaboratively with technical teams, operations, product managers, and business stakeholders to ensure alignment and effective implementation of data initiatives.

• Identify and communicate data quality improvement process automation opportunities.

• Actively contribute and promote a culture of engineering excellence.

Required Skills & Qualifications

• Extensive, hands-on experience working with Salesforce, Siebel CRM, and Oracle ERP.

• Familiarity with marketing and sales automation platforms such as Demandbase, SalesLoft, and HubSpot.

• Demonstrated proficiency in SQL and experience with large-scale data processing frameworks like Hadoop and Spark.

• Experience working with BI/analytics tools, especially Power BI.

• Experience with AI-powered database optimization tools.

• Experience preparing data sets for use in machine learning and AI applications.

• Excellent communication skills, with the ability to present findings and insights to both technical and non-technical audiences in a clear and engaging manner.

• Ability to thrive in a fast-paced, dynamic environment, adjusting to changing priorities while maintaining high-quality standards.

• Proficiency with Salesforce data tools including Data Loader, Workbench, and Inspector.

• Track record of implementing data engineering best practices.

Education & Experience

Education: Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Applied Mathematics, or a related technical field required. A Master’s degree is preferred but not required if equivalent practical experience is demonstrated.

Experience: 5+ years of progressive experience in data engineering, data integration, or backend data platform development, supporting enterprise-scale data ecosystems. Experience must include designing, building, and maintaining complex data pipelines across multiple systems (e.g., CRM, ERP, cloud data platforms), implementing data quality and validation frameworks, and partnering with cross-functional technical and business teams to deliver reliable, analytics-ready data solutions.

Certifications: Cloud and data engineering certifications preferred (e.g., Microsoft Azure Data Engineer Associate, Azure Solutions Architect, or equivalent AWS/GCP credentials). Salesforce certifications related to data architecture or platform development (e.g...