Senior Data Engineer

About Tekion:

Positively disrupting an industry that has not seen any innovation in over 50 years, Tekion has challenged the paradigm with the first and fastest cloud-native automotive platform that includes the revolutionary Automotive Retail Cloud (ARC) for retailers, Automotive Enterprise Cloud (AEC) for manufacturers and other large automotive enterprises and Automotive Partner Cloud (APC) for technology and industry partners. Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform. The transformative platform uses cutting-edge technology, big data, machine learning, and AI to seamlessly bring together OEMs, retailers/dealers and consumers. With its highly configurable integration and greater customer engagement capabilities, Tekion is enabling the best automotive retail experiences ever. Tekion employs close to 3,000 people across North America, Asia and Europe.

About the Role
We’re seeking a Senior Data Engineer  with strong experience in the AWS ecosystem  and SaaS platforms  to design and build scalable, secure, and high-performance data pipelines. You’ll enable analytics, AI/ML, and product insights across large-scale data environments, collaborating closely with data scientists, product managers, and business teams.Key Responsibilities

• Design, develop, and maintain AWS-based data pipelines (S3, Glue, Redshift, Athena, Lambda, Kinesis).
• Build and optimize data lake and data warehouse solutions for SaaS metrics and analytics.
• Implement ETL/ELT workflows using dbt, Airflow, or Step Functions or custom framework.
• Ensure data quality, governance, and lineage across the ecosystem.
• Integrate and process data from various SaaS sources (Salesforce, Stripe, Segment, etc.).
• Partner with AI/ML teams to enable model training, feature engineering, and real-time inference data flows.
• Monitor and tune performance for scalability and cost efficiency.

Required Skills

• 5+ years of experience in data engineering; 3+ years on AWS data stack.
• Proficiency in Python, Pyspark, SQL , and modern data frameworks (Spark, Glue, dbt).
• Strong understanding of SaaS data models , event streaming , and cloud-native architectures .
• Hands-on experience with data governance , security , and compliance  (GDPR/SOC2).
• Familiarity with CI/CD, Git, and infrastructure as code (Terraform/CloudFormation).

Preferred Qualifications

• Experience with AI/ML pipelines , feature stores, or MLOps tooling.
• Exposure to Databricks , AWS EMR , or real-time analytics.
• AWS Data Analytics or Solutions Architect certification.
• Experience with data observability tools and modern SaaS data integrations.