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Bengaluru, Karnātaka, India
Actively hiring, first seen by us todayWork setup in the employer’s posting: On-siteFrom the employer’s posting
Employment type in the employer’s posting: FullTimeFrom the employer’s posting
6+ 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.
Familiarity with CI/CD, Git, and Infrastructure as Code tools is a plus.
Tekion connects the entire spectrum of the automotive retail ecosystem through one seamless platform.
In the employer’s words · Read in context
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 0
Early. Similar jobs usually come down between day 5 and day 54.
From 12,273 similar postings that came down. Coming down is not always a hire.
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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.
- 6+ years of experience in Data Engineering. - Strong expertise in Python, SQL, and Apache Spark. - Experience building scalable batch and real-time ETL/ELT pipelines.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Proficiency in Python and/or Scala for data engineering applications. - Experience with workflow orchestration platforms such as Airflow or similar technologies. Qualifications
- Experience with Delta Lake, Apache Iceberg, or Apache Hudi. - Expertise in workflow orchestration using Airflow. - Experience implementing data quality frameworks and monitoring solutions.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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.
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.
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.
6+ 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.
Competitive compensation.
Generous stock options.
Medical Insurance coverage.
Work with some of the brightest minds from Silicon Valley’s most dominant and successful companies.
Current Tekion Employees: Please apply via the Internal Job Board in Ashby.
Note: Tekion recently transitioned to a new recruiting tool and we appreciate your patience and feedback as we adjust to our new system!
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.
Important: Tekion will only contact candidates from an @tekion.com email address or through our applicant tracking system (no-reply@ashbyhq.com). We may also work with authorized recruiting partners from time to time. Tekion and its recruiting partners will never ask you to pay fees or send money for applications, interviews, training, or onboarding. If you receive a message that seems suspicious, please do not respond or share personal or financial information.
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Bengaluru, Karnātaka, India
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