Senior Data Engineer

Gurgaon, Haryana, India

Actively hiring, first seen by us today

Pay: Pay not listed
Work setting: Not stated
Employment: Not stated

What you’ll work on

Full posting

Build and develop data ingestion pipelines, from requirements and data mapping through deployment
Automate and industrialize build and development tasks
Troubleshoot complex problems and propose innovative solutions
Provide operational support, maintenance and enhancements after go-live
Lead discussion sessions with stakeholders and report project status

From the employer’s posting

data ingestion development, preparing data mapping documentation, testing and deployment

Automate, Industrialize the build and development tasks.

Resolve and troubleshoot problems and complex issues. Provide innovative solutions to complex business problems.

Provide operational support, ongoing maintenance and enhancement after implementation

Lead discussion sessions with stakeholders.

Apply at Orange Business

Posting record

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Actively 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 5, 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

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 6 and day 54.

From 11,032 similar postings that came down. Coming down is not always a hire.

Orange Business is hiring

27 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See 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
SQL
Azure
Databricks
Hadoop
Hive
Kafka
Kubernetes
Power BI
Spark
PySpark

Where the posting names them

- Good experience handling large volume data as well as both structured/unstructured data in Streaming and Batch modes : Kappa, Medallion Architecture, Lambda Architecture - High Coding proficiency in at least one modern programming language: Python, Java or Scala. - Hands on Experience on NiFi , Hive, SQL/HQL, Oozie, Pyspark, Data Bricks

- High Coding proficiency in at least one modern programming language: Python, Java or Scala. - Hands on Experience on NiFi , Hive, SQL/HQL, Oozie, Pyspark, Data Bricks - Good Understanding of Data Integration Patterns : Medallion and Kappa

- Good Understanding of Cloud architecture is must. - Good to be professionally certified in any of the Hyperscalers preferably Azure. - Azure Data Engineering Stack:

- Good to be professionally certified in any of the Hyperscalers preferably Azure. - Azure Data Engineering Stack: - Data Ingestion: UsesAzure Data Factory (ADF) for scheduled batch ETL/ELT orchestration, alongside- Azure Event Hubs and IoT Hub for high-throughput, real-time streaming data (such as app logs,

- Azure Data Engineering Stack: - Data Ingestion: UsesAzure Data Factory (ADF) for scheduled batch ETL/ELT orchestration, alongside- Azure Event Hubs and IoT Hub for high-throughput, real-time streaming data (such as app logs, - clickstreams, or IoT telemetry).

- clickstreams, or IoT telemetry). - Storage Layer: Uses Azure Data Lake Storage (ADLS) Gen2 and Azure Blob Storage as a scalable,- cost-effective foundation to store raw, curated, and enriched data (often structured into a Bronze, - Silver, and Gold medallion architecture).

- Silver, and Gold medallion architecture). - Data Processing & Transformation: Uses Azure Databricks (powered by Apache Spark) for heavy big-data engineering, machine learning, and stream-batch processing. - Data Warehousing & Analytics: Uses Azure Synapse Analytics as a unified platform to query, model, and serve transformed data to Business Intelligence (BI) tools like Power BI.

- Data Processing & Transformation: Uses Azure Databricks (powered by Apache Spark) for heavy big-data engineering, machine learning, and stream-batch processing. - Data Warehousing & Analytics: Uses Azure Synapse Analytics as a unified platform to query, model, and serve transformed data to Business Intelligence (BI) tools like Power BI. - Good knowledge on Azure Data Fabric.

- Data Warehousing & Analytics: Uses Azure Synapse Analytics as a unified platform to query, model, and serve transformed data to Business Intelligence (BI) tools like Power BI. - Good knowledge on Azure Data Fabric. - Good Experience ofAGILE methods (Scrum, Kanban)

- Implementing Best Data Integration Practices. - Good understanding of Big Data Ecosystem with frameworks like HADOOP, SPARK. - Good Understanding of Data Layers : Bronze, Silver, Gold.

- Good Understanding of Data Integration Patterns : Medallion and Kappa - Good understanding of KAFKA, Rabbit MQ. - Good understanding of API concepts : REST and also microservices architecture

- Good understanding of API concepts : REST and also microservices architecture - Good Understanding of Devops toolings and Concepts like Kubernetes, Jenkins, Gitlab - Good to have understanding of ELK stack .

- Good understanding of JIRA. - Good to have understanding of Power BI Reporting. - Understanding of Data Modelling is must

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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 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

View original posting ↗

Publication date : Oct 12, 2026, 12:00AM

Join us at Orange Business!
We are a network and digital integrator that understands the entire value chain of the digital world, freeing our customers to focus on the strategic initiatives that shape their business.
Every day, you will collaborate with a team dedicated to providing consistent, sustainable global solutions, no matter where our customers operate. With over 30,000 employees across Asia, the Americas, Africa, and Europe, we offer a dynamic environment to develop and perfect your skills in a field filled with exciting challenges and opportunities.

As part of the Big Data B2B program, OBS set up a shared Big Data platform and a Data Lake for Use cases exploration and industrialization.

We are looking for Senior Data Engineer 5-8 years of experience in building Data Pipelines with below KRA(S):

Automate, Industrialize the build and development tasks.
Lead discussion sessions with stakeholders.
Participate in all areas of the data Engineering life-cycle,requirements gathering and data mapping, systems design, data ingestion development, preparing data mapping documentation, testing and deployment, post implementation support and monitoring.
Resolve and troubleshoot problems and complex issues.
Provide innovative solutions to complex business problems.
Report to and work closely with project teams and Business Analysis team on project delivery status.
Prepare progress update and status report.
Provide operational support, ongoing maintenance and enhancement after implementation as part of Run Management Activities.
Implementing Best Data Integration Practices.

Good understanding of Big Data Ecosystem with frameworks like HADOOP, SPARK.
Good Understanding of Data Layers : Bronze, Silver, Gold.
Good experience handling large volume data as well as both structured/unstructured data in Streaming and Batch modes : Kappa, Medallion Architecture, Lambda Architecture
High Coding proficiency in at least one modern programming language: Python, Java or Scala.
Hands on Experience on NiFi , Hive, SQL/HQL, Oozie, Pyspark, Data Bricks
Good Understanding of Data Integration Patterns : Medallion and Kappa
Good understanding of KAFKA, Rabbit MQ.
Good understanding of API concepts : REST and also microservices architecture
Good Understanding of Devops toolings and Concepts like Kubernetes, Jenkins, Gitlab
Good to have understanding of ELK stack .
Good to have understanding of Monitoring tools like Prometheus etc.
Good Understanding of Cloud architecture is must.
Good to be professionally certified in any of the Hyperscalers preferably Azure.
Azure Data Engineering Stack:
Data Ingestion: UsesAzure Data Factory (ADF) for scheduled batch ETL/ELT orchestration, alongside
- Azure Event Hubs and IoT Hub for high-throughput, real-time streaming data (such as app logs,
- clickstreams, or IoT telemetry).
Storage Layer: Uses Azure Data Lake Storage (ADLS) Gen2 and Azure Blob Storage as a scalable,
- cost-effective foundation to store raw, curated, and enriched data (often structured into a Bronze,
- Silver, and Gold medallion architecture).
Data Processing & Transformation: Uses Azure Databricks (powered by Apache Spark) for heavy big-data engineering, machine learning, and stream-batch processing.
Data Warehousing & Analytics: Uses Azure Synapse Analytics as a unified platform to query, model, and serve transformed data to Business Intelligence (BI) tools like Power BI.
Good knowledge on Azure Data Fabric.
Good Experience ofAGILE methods (Scrum, Kanban)
Good understanding of JIRA.
Good to have understanding of Power BI Reporting.
Understanding of Data Modelling is must
Understanding of Open Digital Architecture and TMF principles is preferably.
Understanding of Tools Like DSS, Jupiter Notebook is preferably.

You bring a can-do attitude, tackle challenges head-on and challenge the status quo with new and innovative ideas.

Global Opportunities: Work in multi-national teams with opportunity to collaborate with colleagues and customers from all over the world.
Flexible Work Environment: Flexible working hours and possibility to combine work from office and home (hybrid ways of working).
Professional Development: Training programs and upskilling/re-skilling opportunities.
Career Growth: Internal growth and mobility opportunities within Orange.
Caring and Daring Culture: Health and well-being programs and benefits, diversity & inclusion initiatives, CSR and employee connect events.
Reward Programs: Employee Referral Program, Change Maker Awards.

At Orange, only your skills matter.

Regardless of your age, gender, background, origin, religion, sexual orientation, disability, neurodiversity, or appearance, we actively encourage diversity within our teams, as it is a collective strength and a driver of innovation.
Orange is a disability-inclusive employer: please feel free to let us know about any specific needs you may have.

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