Salesforce Data Cloud Engineer – Audience & Activation

New

JobgetherData engineering

Full-time remote position that can be performed from anywhere in India.Full-TimeMiddle

Salary1,500,000 - 1,800,000 INR per year

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Job Details

Experience: 4+ years of professional experience in data engineering, cloud architecture, or a related technical discipline.
Required Skills: AWSSQLSnowflakeAzure

Have 4+ years of professional experience in data engineering, cloud architecture, or a related technical discipline.
Bring hands-on expertise with Salesforce Data Cloud, Data 360, and its core components.
Demonstrate strong SQL proficiency, including manipulating, analyzing, transforming, and reporting on complex datasets.
Have practical experience with Snowflake, AWS, Azure, or Google Cloud Platform (GCP).
Have experience configuring and managing Data Extensions and Data Model Objects (DMOs).
Understand data quality, data integrity, troubleshooting, and governance standards.
Have hands-on experience with Calculated Insights and Computed Traits.
Know consent management, data privacy practices, and relevant regulatory requirements.
Be familiar with Data Streams, real-time ingestion, and continuous data processing architectures.
Have data architecture and integration skills for connecting platforms and source systems.
Be able to translate complex business requirements into practical, scalable technical solutions.
Bring analytical and problem-solving skills and attention to data accuracy and system reliability.

Design, implement, and optimize Calculated Insights and Computed Traits for audience segmentation, targeting, and activation.
Develop, optimize, and maintain complex SQL queries for data extraction, transformation, analysis, and reporting.
Configure and manage Data Extensions for scalable storage and access to customer and business data.
Architect and maintain data pipelines and integrations across Snowflake, AWS, Azure, and GCP.
Configure Salesforce Data Cloud (Data 360) for real-time data ingestion, processing, and activation.
Implement and monitor Data Streams between source systems and the data cloud.
Define and maintain Data Model Objects (DMOs) for data relationships, analytics, and audience use cases.
Assess data quality, investigate discrepancies, and troubleshoot issues affecting data accuracy and integrity.
Establish consent management processes and data governance frameworks for privacy and responsible data use.
Translate business and data requirements into scalable technical solutions.

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