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Senior Data Engineer
Bangalore, IN
Actively hiring, first seen by us today- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and build reliable, scalable ETL/ELT data pipelines
Manage Snowflake data warehousing, modelling and performance tuning
Run large-scale batch and streaming workloads with Spark and Kafka
Prepare structured and unstructured datasets for AI/ML and GenAI workloads
From the employer’s posting
designing reliable and scalable data pipelines
including data warehousing, data modelling, performance optimization, and integration with ETL/ELT pipelines
including large-scale data processing and streaming workloads
Experience preparing and managing structured/unstructured datasets for AI/ML and GenAI workloads
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 10, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
K MART Australia is hiring
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add 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.
- Java
- Python
- Scala
- AWS
- Azure
- Docker
- Kafka
- Kubernetes
- S3
- Snowflake
- Spark
Where the posting names them
- 5–7 years of experience with Big Data technologies such as Apache Spark and Kafka, including large-scale data processing and streaming workloads. - Strong programming experience in Python, with working knowledge of Java or Scala for data engineering applications. - AI / Generative AI experience: Exposure to integrating LLMs into enterprise applications and data platforms, including prompt engineering, embeddings, RAG (Retrieval-Augmented Generation), vector databases, and LLM APIs.
- 5–7 years of overall experience in Data Engineering, building scalable and production-grade data platforms. - 3+ years of hands-on experience with AWS services, including IAM, API Gateway, EC2, S3, and related cloud services. - 2+ years of experience in containerization and orchestration, including creating, deploying, and managing containers using Docker and Kubernetes.
- AI Data Engineering: Experience preparing and managing structured/unstructured datasets for AI/ML and GenAI workloads, including data ingestion, transformation, chunking, metadata management, embeddings, and data quality/governance. - Good to have: Exposure to frameworks and platforms such as LangChain, LangGraph, LlamaIndex, Amazon Bedrock, or Azure OpenAI for developing enterprise GenAI or Agentic AI solutions. -
- 3+ years of hands-on experience with AWS services, including IAM, API Gateway, EC2, S3, and related cloud services. - 2+ years of experience in containerization and orchestration, including creating, deploying, and managing containers using Docker and Kubernetes. - 2+ years of experience building and managing CI/CD pipelines using tools such as Jenkins, GitHub Actions, or equivalent.
- 5–7 years of strong experience with ETL/ELT frameworks and data integration, including designing reliable and scalable data pipelines. - 5–7 years of experience with Big Data technologies such as Apache Spark and Kafka, including large-scale data processing and streaming workloads. - Strong programming experience in Python, with working knowledge of Java or Scala for data engineering applications.
- 2+ years of experience building and managing CI/CD pipelines using tools such as Jenkins, GitHub Actions, or equivalent. - 2+ years of hands-on experience with Snowflake, including data warehousing, data modelling, performance optimization, and integration with ETL/ELT pipelines. - 5–7 years of strong experience with ETL/ELT frameworks and data integration, including designing reliable and scalable data pipelines.
Your next step
Complete your application on jobs.kmart.com.au. The employer’s form will show what is required.
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Demand for Data Engineer roles
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.
About the role
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.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
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.
Job description
Brighter Futures Start Here
At Anko you’ll be joining a diverse team who come together to collaborate globally around tech. We are an innovation hub which power and support our retail brands. You’ll feel the impacts of the work you’ll do for our millions of customers and team members every day. Our brands are focused on being customer-led, digitally enabled retailers, providing you with challenging and rewarding work that you will be proud of.Join our team, choose your own path and work on projects that excite you.
Job Description:
- 5–7 years of overall experience in Data Engineering, building scalable and production-grade data platforms.
- 3+ years of hands-on experience with AWS services, including IAM, API Gateway, EC2, S3, and related cloud services.
- 2+ years of experience in containerization and orchestration, including creating, deploying, and managing containers using Docker and Kubernetes.
- 2+ years of experience building and managing CI/CD pipelines using tools such as Jenkins, GitHub Actions, or equivalent.
- 2+ years of hands-on experience with Snowflake, including data warehousing, data modelling, performance optimization, and integration with ETL/ELT pipelines.
- 5–7 years of strong experience with ETL/ELT frameworks and data integration, including designing reliable and scalable data pipelines.
- 5–7 years of experience with Big Data technologies such as Apache Spark and Kafka, including large-scale data processing and streaming workloads.
- Strong programming experience in Python, with working knowledge of Java or Scala for data engineering applications.
- AI / Generative AI experience: Exposure to integrating LLMs into enterprise applications and data platforms, including prompt engineering, embeddings, RAG (Retrieval-Augmented Generation), vector databases, and LLM APIs.
- Agentic AI: Understanding or hands-on experience building AI agents and agentic workflows, including tool/function calling, multi-step reasoning workflows, orchestration, and integration of agents with enterprise data sources and APIs.
- AI Data Engineering: Experience preparing and managing structured/unstructured datasets for AI/ML and GenAI workloads, including data ingestion, transformation, chunking, metadata management, embeddings, and data quality/governance.
- Good to have: Exposure to frameworks and platforms such as LangChain, LangGraph, LlamaIndex, Amazon Bedrock, or Azure OpenAI for developing enterprise GenAI or Agentic AI solutions.
A place you can belong:
We celebrate the rich diversity of the communities in which we operate and are committed to creating inclusive and safe environments where all our team members can contribute and succeed. We believe that all team members should feel valued, respected, and safe irrespective of your gender, ethnicity, indigeneity, religious beliefs, education, age, disability, family responsibilities, sexual orientation and gender identity and we encourage applications from all candidates.
Source details
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- Pay
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- Location & working pattern
Bangalore, IN
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