Data Engineer

Overview

The Data Engineer will design, build, and maintain end-to-end ETL pipelines that move data from
SQL-based staging systems (source) into Salesforce (destination). This role focuses on ensuring
data quality, performance optimization, and pipeline reliability in high-volume enterprise
environments.

Job Description

Responsibilities
Data Maintenance & Cleaning
• Manage data in staging tables, ensuring accuracy, completeness, and integrity.
• Perform data cleaning, validation, duplicate removal, and restricted picklist handling before
Salesforce loads.
Data Transformation & Integration
• Build and optimize ETL logic to map staging fields into Salesforce objects.
• Use Salesforce Bulk API (v1/v2) for large-scale batch loads with error handling.
• Implement parallel and incremental loading strategies to improve performance.
Pipeline Scheduling & Automation
• Develop automated workflows using SSIS or ADF to move data from staging → Salesforce.
• Implement retry logic, rerouting, and run tables to track load attempts.
• Monitor pipelines and proactively fix failures.
Performance Engineering
• Tune SQL queries, transformations, and data flow tasks for scalability.
• Reduce execution time on large datasets by using partitioning, indexing, and batch
optimization.
Collaboration & Documentation
• Work with Salesforce Developers and QA teams to deliver reliable data pipelines.
• Document pipeline design, error patterns, and reusable frameworks for knowledge sharing.
Skills Required
• Strong SQL (query tuning, stored procedures, performance optimization).
• Strong analytical skills.
• Good communication skills.
Good to Have Skills
• Hands-on with ETL tools (SSIS, Airflow, ADF).
• Experience with Salesforce data loading (objects, Bulk API v1/v2, schema mapping).
• Proficiency in Python or Java for transformations and automation.
• Knowledge of parallel processing, incremental loads, and error handling frameworks.
• Familiarity with version control (Git) and CI/CD tools (Jenkins).

Skills & Requirements

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