Senior Azure Data & Integration Engineer (ADF, SSIS, APIs, iPaaS) - (CF0011)

3 Key Consulting•Thousand Oaks, CA

13d•Hybrid

About The Position

The Senior Data Engineer will be an integral part of the Integrations team within the Information Technology department. They will have the responsibility to design, develop, support, and optimize data pipelines and architectures using modern iPaaS solutions and other cloud-based data processing and storage solutions. They will collaborate with various stakeholders to identify data needs and utilize best practices to integrate with disparate systems for data sharing.

Requirements

5+ years of hands-on experience with Azure Data Factory, Azure SQL offerings, and SSIS.
Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or a related field
Proficiency in SQL, Python, stored procedures and other data transformation techniques.
Expertise in optimizing SQL queries using query optimization techniques and other performance tuning strategies.
Scripting experience utilizing Python/PowerShell.
Experience with system design and data architecture, including scalable integration patterns.
Exposure to modern data platforms such as Databricks, Synapse, BigQuery, or Snowflake.
Experience with iPaaS tools (e.g., SnapLogic, TIBCO, Adeptia) and external system integrations.
Strong problem-solving and data debugging skills.
Demonstrated ability to learn and adapt to new technologies and methodologies.
Excellent communication skills and teamwork abilities.
Candidates must be authorized to work in the United States. This position is not open to new visa sponsorship. Candidates who require employer sponsorship now or in the future will not be considered. H-1B transfer candidates may be considered.

Nice To Haves

Restaurant industry experience.
Familiarity with other cloud-based technologies and services on Azure e.g. Logic Apps, Functions.
Experience building frameworks and utilities that standardize implementation of data quality, logging, monitoring etc.
Azure certifications e.g. Azure Fundamentals, Azure Data Fundamentals, Azure Data Engineer.
Experience mentoring engineers, setting standards, and contributing to technical roadmaps.

Responsibilities

Design, develop, and maintain scalable, fault-tolerant data pipelines using ETL/ELT frameworks to support ingestion, transformation, and integration of structured and unstructured data.
Implement integration solutions with external systems via REST APIs, SOAP services, and message queues (e.g., RabbitMQ and Kafka) to enable real-time and batch data exchange.
Partner cross-functionally with Business Analysts, BI teams, and stakeholders to translate business requirements into technical designs, data contracts, and production-ready solutions.
Optimize and troubleshoot data systems (Azure SQL Database, Azure Data Factory, SSIS) for performance tuning, query optimization, and cost efficiency.
Design and implement robust data models for analytical and transactional systems ensuring referential integrity and scalability.
Implement best practices for data management, including data governance, security (RBAC, password less auth), compliance, and auditing using Azure Purview or similar tools.
Maintain comprehensive documentation of data workflows, architecture diagrams, and integration patterns.
Mentor and support junior engineers through code reviews, design guidance, and troubleshooting, helping raise overall engineering quality and delivery consistency.
Lead proofs of concept (POCs) and evaluate tools such as Snowflake, Databricks, and Airflow, providing recommendations to improve architecture, scalability, and operational maturity.
Leverage CI/CD pipelines for Azure functions, data factory and SSIS using GitHub Actions to ensure automated deployments and version control.
Work with cloud-native storage and compute services (Azure Blob Storage, Data Lake Gen2, Functions, Logic Apps, SSIS,ADF) for scalable data processing and integration.
Develop automation scripts in Python and PowerShell for data processing, orchestration, and operational efficiency.