Senior Software Engineer

About the role

You will architect and evolve a multi-tenant, cloud-scale data platform that serves thousands of dealerships and business users while maintaining strong tenant isolation, governance, and data quality standards. You will design and drive the implementation of near real-time and real-time data ingestion architectures, shifting the platform from batch-oriented processing to support faster decision-making. In this role, you will own the core data engineering components that power analytical products, operational insights, and emerging AI-driven experiences across the Tekion platform. You will collaborate closely with data scientists, product teams, and enterprise stakeholders to translate business requirements into scalable data solutions. Your work will directly shape the enterprise data foundation that underpins analytics and AI use cases for the global automotive retail ecosystem. You will apply deep expertise to solve complex multi-tenant data challenges at scale, ensuring reliability, performance, and security. This position offers the opportunity to make a lasting impact on the future of analytics and data infrastructure in the automotive industry.

Key facts

What you'll do

Design and build scalable data platforms, data warehouses, and lakehouse architectures that support enterprise-wide analytics.

Provide deep expertise in data modeling, including dimensional modeling, Data Vault, and enterprise data architecture principles to define robust data structures.

Write advanced SQL with a focus on query optimization, performance tuning, and large-scale data processing to meet demanding SLAs.

Develop hands-on experience with distributed data processing frameworks such as Apache Spark to handle complex transformations at scale.

Implement and manage modern lakehouse technologies such as Delta Lake, Apache Iceberg, or Apache Hudi to ensure efficient data storage and querying.

Design and implement batch, streaming, and CDC-based data ingestion pipelines that support real-time use cases and operational needs.

Demonstrate proficiency in Python and/or Scala for building data engineering applications, libraries, and automation scripts.

Leverage workflow orchestration platforms such as Airflow or similar technologies to schedule, monitor, and manage data pipelines reliably.

Partner with data scientists, analysts, and product teams to deliver data solutions that drive AI, machine learning, and advanced analytics initiatives.

Implement data quality frameworks and monitoring solutions to ensure accuracy, consistency, and trust in enterprise data assets.

Optimize data partitioning, schema evolution, and performance tuning strategies to handle growing data volumes and evolving requirements.

Contribute to architectural decisions that support scalability, resilience, and security in a multi-tenant cloud environment.

Collaborate with cross-functional stakeholders to define data standards, governance policies, and best practices for data management.

Engage with modern CI/CD, Git, and Infrastructure as Code tools to enable reliable and repeatable deployment of data platform components.

Continuously evaluate emerging technologies and patterns to evolve the data platform in line with business and innovation goals.

Requirements

6+ years of professional experience in Data Engineering with a strong track record of delivering scalable data solutions.

Strong expertise in Python, SQL, and Apache Spark, with the ability to write efficient and maintainable code.

Demonstrated experience building scalable batch and real-time ETL/ELT pipelines that support high-volume data processing.

Hands-on experience with AWS services including EMR, S3, Glue, and Athena for data platform implementation and operations.

Experience with Kafka, Flink, or Kinesis for streaming data processing and event-driven architectures.

Solid understanding of dimensional modeling, Data Vault, and data warehousing concepts to structure effective data models.

Hands-on experience with Delta Lake, Apache Iceberg, or Apache Hudi for lakehouse implementations and data management.

Expertise in workflow orchestration using Airflow or equivalent tools to manage dependencies and pipeline execution.

Experience implementing data quality frameworks and monitoring solutions to detect and resolve data issues proactively.

Strong understanding of partitioning strategies, schema evolution, and performance optimization techniques for large-scale datasets.

Familiarity with CI/CD, Git, and Infrastructure as Code tools is a plus for modern engineering practices.

Ability to work effectively in a collaborative, multi-tenant environment with clear communication and stakeholder management.

Commitment to maintaining high standards of data governance, security, and compliance within the platform.

Willingness to contribute to architectural discussions and guide best practices for data engineering across the organization.

Practical notes

Effective 4 Aug 2026, Current Tekion Employees should apply via the Internal Job Board in Ashby

Tekion is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, victim of violence or having a family member who is a victim of violence, the intersectionality of two or more protected categories, or other applicable legally protected characteristics.

For more information on our privacy practices, please refer to our Applicant Privacy Notice here https://tekion.com/legal/privacy/applicant-and-candidate-privacy-notice.