Sr. Data Engineer

Objectstream•Oklahoma City, OK

10h•Onsite

About The Position

Objectstream is seeking a Senior Data Engineer to lead a strategic data migration initiative that moves structured and semi-structured data from Microsoft Azure Blob Storage into Salesforce, with the platform surface delivered through Salesforce Experience Cloud. This role sits at the intersection of cloud data engineering, data quality management, and CRM integration, requiring both technical depth and a sharp analytical mindset. The source data landscape is heterogeneous: schemas may be inconsistent, field names will differ, data types may require transformation, and business logic must be applied before records can be loaded into Salesforce objects. You will own the end-to-end migration pipeline, from raw ingestion and profiling through cleansing, transformation, schema mapping, and final load validation.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
8+ years of experience in data engineering, ETL development, or data migration roles
Demonstrated experience migrating data into Salesforce, including use of Bulk API 2.0, Data Loader, or similar tooling
Hands-on experience with Azure Blob Storage and Azure Data Factory
Proficiency in Python for data transformation, particularly pandas, PySpark, or similar libraries
Strong SQL skills with experience querying, profiling, and transforming large datasets
Experience with cross-schema or heterogeneous data mapping where source and target structures differ significantly
Familiarity with Salesforce data model fundamentals: standard objects, relationships, sharing model, and record types
Understanding of Salesforce Experience Cloud portal data scoping and community user access patterns
Experience implementing data quality frameworks: validation rules, rejection workflows, and audit logging
Proficiency with Git and version-controlled development practices

Nice To Haves

Salesforce Certified Administrator or Platform App Builder certification
Experience with Salesforce CLI (sf / sfdx) for data operations and org management
Familiarity with Apache Airflow or similar workflow orchestration platforms
Experience with dbt for data transformation documentation and lineage
Experience with data cataloging and lineage tools
Familiarity with Salesforce MuleSoft

Responsibilities

Connect to Azure Blob Storage containers and extract files across formats including CSV, Parquet, JSON, and Avro
Profile source datasets to identify schema drift, null patterns, cardinality anomalies, and referential integrity gaps
Document data dictionaries and lineage maps for all source-to-target field mappings
Design and implement cross-schema mapping logic where source table structures do not align with Salesforce standard or custom objects
Build transformation pipelines using Azure Data Factory, or equivalent ETL tooling to normalize, reshape, and enrich source data
Apply business rules and data derivation logic to generate missing or computed fields required by Salesforce objects
Handle many-to-one and one-to-many relationship resolution between source tables and Salesforce object hierarchies (Accounts, Contacts, Cases, custom objects)
Detect and remediate duplicate records, invalid formats, out-of-range values, broken foreign keys, and encoding inconsistencies
Implement data quality scoring and rejection workflows with clear audit trails for records that fail validation thresholds
Collaborate with business stakeholders to define and codify data quality rules and acceptable transformation logic
Produce data quality reports pre- and post-migration to demonstrate completeness and accuracy
Load transformed data into Salesforce using Bulk API 2.0, Data Loader, or Salesforce CLI with appropriate error handling and retry logic
Work within the Salesforce Experience Cloud data model to ensure migrated records are correctly scoped to the right communities, portals, and sharing rules
Manage external ID strategies, upsert operations, and record ownership assignment during migration
Coordinate with Salesforce admins and developers to validate object relationships, validation rules, triggers, and process automation that may affect data loading
Design idempotent, resumable migration pipelines capable of incremental and full-load modes
Implement orchestration and scheduling using Azure Data Factory or Apache Airflow
Build monitoring, alerting, and logging infrastructure for pipeline health and data throughput
Write and maintain infrastructure-as-code and pipeline configuration in version-controlled repositories
Communicate migration progress, blockers, and data quality findings to technical and non-technical stakeholders
Partner with Salesforce Experience Cloud administrators to align portal data structures with migrated records
Contribute to post-migration hypercare activities, including reconciliation validation and end-user data access verification