Senior Data & Integration Engineer

The Senior Data and Integration Engineer is a senior technical role responsible for architecting, developing, and optimizing enterprise data and integration solutions that enable seamless, reliable data flow across Parker’s Kitchen’s technology ecosystem. This role serves as a technical leader and subject matter expert in ETL/ELT pipeline design, API integration architecture, data warehousing strategy, and cloud-based data platforms. The ideal candidate will drive technical standards, mentor junior engineers, and work closely with business stakeholders, developers, and data teams to deliver scalable, high-quality data infrastructure that supports operational excellence and strategic decision-making.

ESSENTIAL DUTIES AND RESPONSIBILITIES

Data Architecture & Pipeline Engineering:

• Architect, develop, and maintain complex ETL/ELT pipelines to extract, transform, and load data from multiple sources into data lakes and data warehouses, ensuring scalability and fault tolerance.
• Define and enforce data transformation standards to ensure data quality, consistency, and performance across all pipelines.
• Automate data ingestion and transformation processes using tools such as Azure Data Factory (ADF), Apache Airflow, SSIS, or equivalent platforms.
• Evaluate emerging data technologies and recommend adoption strategies aligned with organizational goals.
• Design and implement data lake and Lakehouse architectures to support analytics, reporting, and operational workloads.

Integration Architecture & API Development:

• Design, develop, and govern API-based integrations between enterprise applications, cloud platforms, and third-party services, establishing reusable integration patterns.
• Work with RESTful and SOAP APIs, JSON, XML, webhooks, and event-driven architectures.
• Implement and enforce authentication and security protocols (OAuth 2.0, JWT, API keys, mTLS) across all integration points.
• Define integration architecture standards, including error handling, retry logic, rate limiting, and monitoring practices.
• Lead integration efforts for new vendor platforms and system migrations, serving as the technical point of contact.

Database Engineering & Cloud Platforms:

• Design and optimize database structures for data warehousing, reporting, and real-time analytics solutions.
• Write and optimize complex SQL queries, stored procedures, views, and materialized views to support data extraction and analytics workloads.
• Work with relational databases (SQL Server, PostgreSQL, Snowflake) and NoSQL solutions, recommending the appropriate technology for each use case.
• Develop and deploy data solutions in cloud environments (primarily Azure), leveraging cloud storage, compute services, and serverless technologies for scalable data processing.
• Contribute to Infrastructure as Code (Terraform, ARM templates) and CI/CD pipeline development for data platform deployments.

Data Governance, Security & Compliance:

• Implement and champion data governance best practices, including metadata management, data lineage tracking, data cataloging, and access controls.
• Ensure compliance with data privacy regulations (PCI DSS, state privacy laws) and organizational security policies.
• Define and monitor data quality metrics, SLAs, and alerting thresholds for all production data pipelines.
• Conduct security reviews of data integrations and recommend hardening measures.

Technical Leadership & Collaboration:

• Serve as a technical mentor and resource for peers and cross-functional teams on data engineering best practices.
• Create and maintain technical documentation, architecture diagrams, runbooks, and process workflows.
• Lead troubleshooting and root cause analysis for data integration failures and performance degradation.
• Support cross-functional teams in identifying data-related issues and translating business requirements into technical solutions.
• Participate in architecture review boards and contribute to the organization’s technology roadmap.
• Drive continuous improvement initiatives to reduce technical debt and improve pipeline reliability and performance.

EDUCATION AND REQUIREMENTS

Required:

• Bachelor’s degree in computer science, Information Systems, Data Engineering, or a related field.
• 5+ years of progressive experience in data engineering, data integration, or related roles, with demonstrated ownership of enterprise-scale solutions.
• Deep expertise in ETL/ELT tools (Azure Data Factory, Apache Airflow, SSIS, Informatica, or equivalent).
• Advanced SQL proficiency and strong experience with database technologies (SQL Server, Snowflake, PostgreSQL).
• Extensive hands-on experience designing and consuming APIs, web services, and integration platforms.
• Strong experience with cloud data platforms, preferably Azure (Synapse, Data Lake Storage, Functions).
• Proficiency in scripting languages (Python, PowerShell, or Bash) for automation and data processing.
• Experience with DevOps practices, CI/CD pipelines, and Infrastructure as Code (Terraform, ARM templates).
• Proven ability to lead technical initiatives, define standards, and influence architecture decisions.
• Strong problem-solving, analytical, and communication skills with the ability to translate complex technical concepts for business stakeholders.

Preferred:

• Experience in retail, convenience store, or food service technology environments.
• Experience with data observability and pipeline monitoring tools.
• Knowledge of event-driven architecture, message queues (Kafka, Azure Service Bus), and stream processing.
• Experience with Snowflake administration, optimization, and Snowpark.
• Relevant certifications (Azure Data Engineer Associate, Snowflake SnowPro, AWS Data Analytics, etc.)

Physical Requirements:

• Office environment with occasional requirements to work outside of normal business hours.
• On-call rotation for data platform emergencies and critical pipeline failures.
• Ability to lift and carry up to 50 pounds.
• Ability to work in confined spaces and to climb ladders and stairs.