Senior Architect, Software Engineering

40 Minutes ago • 15 Years +

Software Development & Engineering

Job Description

Tekion is seeking a hands-on Senior Data Architect to design and modernize scalable, AI-ready data platforms on the cloud. The role involves designing and implementing data architecture and pipelines using PySpark, Python, and AWS services, modernizing legacy Java-based ETL systems to Spark, and building data lakes and warehouses optimized for analytics and AI/ML. The architect will collaborate with data scientists, define HLD/LLD, and implement standards for data quality, governance, and security.

Must Have:

Design and implement data architecture and pipelines using PySpark, Python, and AWS services (Glue, EMR, S3, Redshift, Athena).
Modernize legacy Java-based migration or ETL scripts into Spark-based solutions.
Build and manage data lakes and data warehouses optimized for analytics and AI/ML workflows.
Define and document HLD (High-Level Design) and LLD (Low-Level Design) for scalable data systems.
Implement standards for data quality, governance, performance optimization, and security.
Lead troubleshooting, performance tuning, and architecture reviews for data pipelines.
15+ years of experience in data engineering or architecture with strong hands-on development.
Expert-level proficiency in PySpark, Python, and SQL.
Strong understanding of AWS data ecosystem (Glue, EMR, S3, Redshift, Lambda).
Proven experience migrating or re-engineering Java-based ETL systems into modern Spark environments.
Solid foundation in data lake, data warehouse, and cloud-native architecture design.
Experience supporting AI/ML data pipelines and integrating data platforms with ML workflows.
Experience with RDBMS (Maria DB/MySQL) and No-SQL database (MongoDB).
Experience with GIT, Jenkins, & AWS.

Add these skills to join the top 1% applicants for this job

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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.

Job Description

We’re seeking a hands-on Senior Data Architect to design and modernize scalable, AI-ready data platforms across cloud. The ideal candidate has deep technical expertise in AWS, PySpark, and Python, and experience migrating legacy Java-based scripts to Spark frameworks while ensuring data quality, scalability, and performance.

Key Responsibilities

Design and implement data architecture and pipelines using PySpark, Python, and AWS services (Glue, EMR, S3, Redshift, Athena).
Modernize legacy systems by converting Java-based migration or ETL scripts into Spark-based solutions.
Build and manage data lakes and data warehouses optimized for analytics and AI/ML workflows.
Collaborate with data scientists and analysts to enable model training, deployment, and continuous data delivery.
Define and document HLD (High-Level Design) and LLD (Low-Level Design) for scalable data systems.
Implement standards for data quality, governance, performance optimization, and security.
Lead troubleshooting, performance tuning, and architecture reviews for data pipelines.

Skills and Experience

15+ years of experience in data engineering or architecture, with strong hands-on development background.
Expert-level proficiency in PySpark, Python, and SQL for data processing and transformation.
Strong understanding of AWS data ecosystem — including Glue, EMR, S3, Redshift, and Lambda.
Proven experience migrating or re-engineering Java-based ETL systems into modern Spark environments.
Solid foundation in data lake, data warehouse, and cloud-native architecture design.
Experience supporting AI/ML data pipelines and integrating data platforms with ML workflows.
Strong documentation skills (HLD, LLD) and ability to communicate architecture clearly to technical and business stakeholders.
Experience with both RDBMS such as Maria DB/MySQL and No-SQL database such MongoDB
Experience with GIT, Jenkins, & AWS
Expertise in performance optimization and cost management for cloud environments
Ability to manage multiple projects and priorities in a fast-paced environment
AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional