Key ResponsibilitiesSalesforce Data Engineering & AnalysisPipeline Architecture

- Build scalable ETL/ELT pipelines to ingest, transform, and synchronize large datasets into Salesforce.
- Design integration solutions between Salesforce and enterprise applications using modern APIs and middleware platforms.

Advanced Analytics

- Conduct deep-dive data analysis using SQL, Python, DBAmp to identify data quality issues, trends, and anomalies.
- Develop data-driven insights that support business operations and strategic initiatives.

Data Modelling

- Design, optimize, and maintain Salesforce standard and custom objects.
- Create scalable data models that support reporting, analytics, and business intelligence requirements.

Data Governance

- Implement automated data quality controls, deduplication processes, and data cleansing frameworks.
- Enforce data governance, security, compliance, and retention policies across Salesforce platforms.

Performance Optimization

- Monitor and optimize data integration processes, APIs, and Salesforce data operations.
- Improve system scalability and data processing efficiency.

Required Tools & Technical SkillsetSalesforce Ecosystem

Data Management

- Salesforce Sales Cloud, Service Cloud, Data Cloud
- Data Loader
- Bulk API 2.0
- Platform Events
- Change Data Capture (CDC)

Querying & Development

- Expert-level SOQL and SOSL
- Apex programming and Apex collections
- Salesforce REST and SOAP APIs

Security & Architecture

- Deep understanding of Salesforce Data Model and Schema
- Salesforce Shield (Data Encryption)
- Role Hierarchies, Sharing Rules, Permission Sets, and Data Security best practices

Core Data Engineering & AnalyticsLanguages

- Expert-level SQL
- Proficiency in Python (Pandas, Num Py) for data analysis and transformation

Data Warehousing & Integration





- Snowflake
- Big Query
- Oracle Database
- SQL Server
- Data integration and ETL/ELT frameworks

BI & Analytics Tools

- Power BI
- Tableau
- Salesforce CRM Analytics

Dev Ops & Methodology

Tools

- Git
- Git Hub
- Git Lab

Process

- CI/CD deployment pipelines
- Agile/Scrum development methodologies
- Data Ops and Dev Ops best practices

Qualifications & ExperienceExperience

- 7–9+ years of experience in Data Engineering, Salesforce Data Architecture, Data Integration, or CRM Data Management.

Education

- Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field.

Problem Solving

- Proven track record delivering large-scale Salesforce data migration, integration, and transformation projects.

Communication

- Ability to translate complex data structures and technical concepts into business-friendly insights for stakeholders.

We have excellent people here and are looking for more. Come join us!

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Equal Employment Opportunities at First Advantage
First Advantage is an equal opportunity employer. We are committed to providing a workplace and recruitment process that is free from unlawful discrimination, harassment, and retaliation. Employment decisions at First Advantage are based solely on qualifications, merit, and business needs. We do not discriminate in any aspect of employment on the basis of race, color, national origin, ancestry, citizenship, religion, creed, sex, gender identity, gender expression, sexual orientation, marital or family status, pregnancy, age, physical or mental disability, medical condition, genetic information, veteran or military status, or any other characteristic protected by applicable law.

Originally posted on Himalayas

📌 Senior Salesforce Data Engineer (India)
🏢 First Advantage
📍 India