Data Engineer III

itel

Senior Data Engineer leading the design and development of scalable data infrastructure and pipelines. Collaborating cross-functionally and implementing best practices for high-quality data engineering.

Posted 6/30/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing scalable data pipelines using Azure Databricks, Azure Data Factory, and SQL Server, while applying data modeling methodologies such as Kimball and Inmon. Proficient in optimizing data performance and ensuring data governance, quality, and compliance standards.

Highest-signal resume keywords

Azure DatabricksAzure Data FactorySQL ServerData ModelingPython

ATS Keywords

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Hard Skills

Data Pipeline DevelopmentETL/ELT DevelopmentDatabase AdministrationPerformance TuningData Workflow ImplementationData QualityData GovernanceAPI IntegrationData ArchitectureCloud Data Platforms

Soft Skills

MentorshipKnowledge SharingCross-Functional Collaboration

Tools & Technologies

SalesforceGitCI/CD PipelinesAzure Data Lake

Industry Keywords

Data EngineeringCloud ServicesData ProcessingData StorageTechnical Debt

Tech Stack

Tools & technologies

AzureCloudETLPythonScalaSQL

About the role

Key responsibilities & impact

Lead the design, development, and implementation of scalable data pipelines and infrastructure using Azure Databricks, Azure Data Factory, SQL Server, Salesforce integrations, and related technologies
Develop and maintain both OLTP and dimensional data models based on business requirements, applying Kimball and Inmon methodologies as appropriate
Optimize data storage and retrieval performance across SQL Server and cloud data platforms
Integrate data from Salesforce and other SaaS applications via APIs and extraction workflows
Implement and maintain batch and real-time data processing architectures
Participate in code and architecture reviews to ensure adherence to data engineering standards and best practices
Analyze and troubleshoot data pipeline and performance issues, providing timely and effective solutions
Contribute to the continuous improvement of data engineering practices, tools, and processes
Stay current with emerging trends in cloud data platforms and identify opportunities for innovation
Champion comprehensive documentation of data architecture, lineage, and modeling decisions
Facilitate knowledge sharing and mentorship across the team; engage cross-functionally to align on architectural vision
Drive adoption of best practices including data governance, quality, security, and compliance standards
Lead initiatives to reduce technical debt and improve pipeline performance and cost efficiency.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field
At least five (5) years of experience in data engineering or a related field
Three (3) or more years of hands-on experience with Azure cloud services including Azure Databricks, Azure Data Factory, and Azure Data Lake
Two (2) or more years of specific experience with the Databricks platform, including ETL/ELT pipeline development, cluster management, and data workflow implementation
Advanced proficiency with SQL Server including database administration, performance tuning, and stored procedures
Strong proficiency in Python and/or Scala for data processing and automation
Demonstrated expertise in conceptual, logical, and physical data modeling including star schema, snowflake schema, SCD Types 1/2/3, and medallion architecture patterns
Experience with Salesforce data architecture and API-based data extraction
Proficiency with Git workflows and CI/CD pipeline development
Strong understanding of data engineering principles, data quality, and best practices.

Benefits

Comp & perks

Flexible work arrangements