Data Engineer with Salesforce

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer with Salesforce based in India.

This role offers the opportunity to build and optimize enterprise-scale data solutions within a highly collaborative digital integration and optimization environment. You will design, maintain, and enhance critical data pipelines connecting CRM, ERP, cloud, and business systems. Your work will directly support marketing, sales, customer support, analytics, and reporting teams with reliable, high-quality data. You will combine data engineering expertise with strong Salesforce knowledge to improve data workflows, governance, and automation. The position involves close collaboration with technical teams, product managers, operations, and business stakeholders. You will also contribute to data quality initiatives and prepare datasets for advanced analytics, machine learning, and AI applications. This is an impactful opportunity to promote engineering excellence while helping create a more data-driven organization.

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Accountabilities:

• Profile data across core revenue operations and go-to-market systems to assess data quality, consistency, completeness, and reliability.

• Design, build, deploy, monitor, and maintain scalable data workflows across Salesforce, Siebel CRM, Oracle ERP, SQL Server, and Azure Cloud data sources.

• Engineer and enhance robust data pipelines and automated transformation processes using SQL and large-scale data processing technologies such as Python, Hadoop, and Spark.

• Develop and maintain database scripts, triggers, functions, and stored procedures to support enterprise data workflows.

• Create automated testing and validation procedures that strengthen data quality management and compliance with data governance standards.

• Collaborate with cross-functional teams to understand data requirements, stakeholder needs, and the impact of technical decisions on analytics and reporting.

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

• Identify opportunities to automate and improve data quality processes, workflows, and operational practices.

• Support the continuous adoption of data engineering best practices and contribute to a culture of engineering excellence.

Requirements:

• You have a Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Software Engineering, Applied Mathematics, or a related technical field; a Master’s degree is preferred but not required when equivalent practical experience is demonstrated.

• You have at least 5 years of progressive experience in data engineering, data integration, or backend data platform development within enterprise-scale data environments.

• You have hands-on experience designing, building, and maintaining complex data pipelines across multiple systems, including CRM, ERP, and cloud data platforms.

• You have extensive experience working with Salesforce, Siebel CRM, and Oracle ERP, along with proficiency in Salesforce data tools such as Data Loader, Workbench, and Inspector.

• You are highly proficient in SQL and experienced with large-scale data processing frameworks such as Hadoop and Spark.

• You have familiarity with marketing and sales automation platforms such as Demandbase, SalesLoft, and HubSpot.

• You have experience with BI and analytics tools, particularly Power BI, as well as AI-powered database optimization tools.

• You have experience preparing high-quality datasets for machine learning and AI applications and implementing data quality and validation frameworks.

• You have a strong understanding of data engineering best practices and a proven track record of applying them in complex environments.

• You communicate clearly and confidently with both technical and non-technical audiences and can present findings and insights in an engaging manner.

• You are adaptable, analytical, and comfortable working in a fast-paced environment where priorities can change while maintaining high quality standards.

• Cloud and data engineering certifications are preferred, including Microsoft Azure Data Engineer Associate, Azure Solutions Architect, or equivalent AWS/GCP credentials.

• Salesforce certifications such as Data Architecture & Management Designer, Platform Developer I, or Salesforce Administrator are considered an advantage, as are certifications in analytics, databases, Power BI, SQL, Hadoop, or Spark.

• You are able to align your working hours with UK business hours.

Benefits:

• Professional development opportunities, including access to an award-winning manager development program.

• Generous Paid Time Off program, subject to applicable eligibility requirements.

• Volunteer Time Off opportunities supporting participation in philanthropic activities.

• Competitive benefits, including medical and dental coverage, subject to applicable eligibility requirements.

• Access to a Global Employee Assistance Program.

• Opportunities to connect with colleagues through six Employee Impact Groups and employee experience events.

• Exposure to innovative data, cloud, automation, machine learning, and AI initiatives within a global technology environment.

• Opportunities to contribute to meaningful data transformation and engineering excellence initiatives.

\nHow Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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