Senior Data Engineer

Job Purpose

We're seeking a talented Senior Data Engineer to join our Enterprise Architecture team in a cross-cutting role that will help define and implement our next-generation data platform. In this pivotal position, you'll lead the design and implementation of scalable, self-service data pipelines with a strong emphasis on data quality and governance. This is an opportunity to shape our data engineering practice from the ground up, working directly with key stakeholders to build mission-critical ML and AI data workflows.

About Our Technology Stack

You'll be working with a modern, on-premises data stack that includes:

• Apache Airflow for workflow orchestration (self-hosted on Kubernetes)
• dbt for data transformation and testing
• Apache Flink for stream processing and real-time data workflows
• Kubernetes for containerized deployment and scaling
• Git-based version control and CI/CD for data pipelines
• Oracle Exadata for data warehousing
• Kafka for messaging and event streaming

We emphasize building systems that are maintainable, scalable, and focused on enabling self-service data access while maintaining high standards for data quality and governance.

Responsibilities

• Design, build, and maintain our on-premises data orchestration platform using Apache Airflow, dbt, and Apache Flink
• Create self-service capabilities that empower teams across the organization to build and deploy data pipelines without extensive engineering support
• Implement robust data quality testing frameworks that ensure data integrity throughout the entire data lifecycle
• Establish data engineering best practices, including version control, CI/CD for data pipelines, and automated testing
• Collaborate with ML/AI teams to build scalable feature engineering pipelines that support both batch and real-time data processing
• Develop reusable patterns for common data integration scenarios that can be leveraged across the organization
• Work closely with infrastructure teams to optimize our Kubernetes-based data platform for performance and reliability
• Mentor junior engineers and advocate for engineering excellence in data practices

Knowledge and Experience

• 5+ years of professional experience in data engineering, with at least 2 years working on enterprise-scale data platforms
• Deep expertise with Apache Airflow, including DAG design, performance optimization, and operational management
• Strong understanding of dbt for data transformation, including experience with testing frameworks and deployment strategies
• Experience with stream processing frameworks like Apache Flink or similar technologies
• Proficiency with SQL and Python for data transformation and pipeline development
• Familiarity with Kubernetes for containerized application deployment
• Experience implementing data quality frameworks and automated testing for data pipelines
• Knowledge of Git-based workflows and CI/CD pipelines for data applications
• Ability to work cross-functionally with data scientists, ML engineers, and business stakeholders

Preferred Knowledge and Experience

• Experience with self-hosted data orchestration platforms (rather than managed services)
• Background in implementing data contracts or schema governance
• Knowledge of ML/AI data pipeline requirements and feature engineering
• Experience with real-time data processing and streaming architectures
• Familiarity with data modeling and warehouse design principles
• Prior experience in a technical leadership role

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