Staff Software Engineer - Data engineer

Posted Yesterday
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Artificial Intelligence • Cloud • Machine Learning • Retail • Software
The Role
Design and evolve a multi-tenant, cloud-scale data platform and lakehouse; build batch, near real-time, and CDC ingestion pipelines; implement data modeling, warehousing, governance, and data quality; optimize large-scale SQL/Spark processing; use Python/Scala, Airflow, AWS services and streaming technologies to enable analytics and AI use cases.
Summary Generated by Built In
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.

Why This Role Matters 
Join us in building the next generation of data intelligence capabilities for the automotive industry. This role goes beyond traditional data engineering and offers the opportunity to shape the enterprise data foundation that powers analytical products, operational insights, and emerging AI-driven experiences across the platform. 
You will play a key role in designing and evolving 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. 
As part of our modernization journey, you will help drive the evolution from batch-oriented data processing to near real-time and real-time data ingestion architectures, enabling faster decision-making and unlocking new AI and machine learning use cases across the business. 

If you are passionate about building large-scale data platforms, solving complex multi-tenant data challenges, and creating the data foundation that powers the future of analytics and AI, this role offers the opportunity to make a lasting impact. 

 
Technical Expertise 
 

  • Strong experience in designing and building scalable data platforms, data warehouses, and lakehouse architectures. 
  • Deep expertise in data modeling, including dimensional modeling, Data Vault, and enterprise data architecture principles. 
  • Advanced SQL skills with experience in query optimization, performance tuning, and large-scale data processing. 
  • Hands-on experience with distributed data processing frameworks such as Apache Spark. 
  • Strong understanding of modern lakehouse technologies such as Delta Lake, Apache Iceberg, or Apache Hudi. 
  • Experience designing and implementing batch, streaming, and CDC-based data ingestion pipelines. 
  • Proficiency in Python and/or Scala for data engineering applications. 
  • Experience with workflow orchestration platforms such as Airflow or similar technologies. 

 

Desired Skills & Experience

  • 7+ years of experience in Data Engineering.
  • Strong expertise in Python, SQL, and Apache Spark.
  • Experience building scalable batch and real-time ETL/ELT pipelines.
  • Hands-on experience with AWS services including EMR, S3, Glue, and Athena.
  • Experience with Kafka, Flink, or Kinesis for streaming data processing.
  • Strong knowledge of dimensional modeling, Data Vault, and data warehousing concepts.
  • Experience with Delta Lake, Apache Iceberg, or Apache Hudi.
  • Expertise in workflow orchestration using Airflow.
  • Experience implementing data quality frameworks and monitoring solutions.
  • Strong understanding of partitioning, schema evolution, and performance optimization.
  • Familiarity with CI/CD, Git, and Infrastructure as Code tools is a plus.

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.

Skills Required

  • Designing and building scalable data platforms, data warehouses, and lakehouse architectures
  • Deep expertise in data modeling including dimensional modeling and Data Vault
  • Advanced SQL skills with query optimization, performance tuning, and large-scale data processing
  • Hands-on experience with distributed data processing frameworks such as Apache Spark
  • Experience with modern lakehouse technologies such as Delta Lake, Apache Iceberg, or Apache Hudi
  • Designing and implementing batch, streaming, and CDC-based data ingestion pipelines
  • Proficiency in Python and/or Scala for data engineering
  • Experience with workflow orchestration platforms such as Airflow
  • 7+ years of experience in Data Engineering
  • Experience building scalable batch and real-time ETL/ELT pipelines
  • Hands-on experience with AWS services including EMR, S3, Glue, and Athena
  • Experience with Kafka, Flink, or Kinesis for streaming data processing
  • Experience implementing data quality frameworks and monitoring solutions
  • Strong understanding of partitioning, schema evolution, and performance optimization
  • Familiarity with CI/CD, Git, and Infrastructure as Code tools

Tekion Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tekion and has not been reviewed or approved by Tekion.

  • Healthcare Strength Healthcare coverage includes 100% employer-paid medical, dental, and vision for many U.S. roles, often extending to families. Additional options like HSA/FSA and pet insurance are cited as part of a robust health offering.
  • Fair & Transparent Compensation Pay is considered competitive overall, with total rewards (pay, stock, equity, and benefits) frequently viewed favorably. Many accounts characterize compensation as strong alongside comprehensive benefits.
  • Wellbeing & Lifestyle Benefits Perks such as free meals/snacks, wellness resources, and on-site amenities are highlighted. Flexible or remote options are available for some roles, adding convenience and flexibility.

Tekion Insights

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The Company
HQ: Pleasanton, CA
1,858 Employees
Year Founded: 2016

What We Do

At Tekion, we believe that business applications don’t have to be boring. In fact, they should be simple, fun and cool! They should be as delightful to use as your favorite social or consumer application, yet powerful enough to seamlessly and efficiently run global businesses that provide unparalleled consumer experience without compromise. Founded by visionary entrepreneur and innovator Jay Vijayan, we are building the world’s best business applications on the cloud starting with the automotive retail industry. We inherently use cutting-edge technologies like big data, machine learning/AI, and human computer interaction (voice, touch, vision, sensors and IoT). We are inventing new technology along the way to overcome barriers and solve big problems, all while having a blast doing it! Our flagship product offering, Automotive Retail Cloud ™- an industry-first cloud-native retail platform, including all functionalities of a Dealer Management System (DMS) launched recently.

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