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Senior Data Engineer (Real-Time Data Processing & Streaming)

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting
  • Design and maintain real-time and near-real-time data processing pipelines

  • Implement streaming solutions with Apache Kafka, Flink, and Spark

  • Develop Java services that process data received from physical devices

  • Build event-driven integrations and ensure reliable delivery to downstream consumers

  • Modernize legacy data processing components toward Kafka-based streaming

From the employer’s posting
Design, develop, and maintain scalable real-time and near-real-time data processing pipelines.
Implement streaming data processing solutions using technologies such as Apache Kafka, Apache Flink, and Apache Spark.
Develop and maintain Java-based services and integration components for processing data received from physical devices.
Ensure reliable data delivery to downstream consumers, applications, and storage systems.
Contribute to the modernization and migration of legacy data processing components toward Kafka-based streaming architectures.

What you’ll bring

All qualifications

Core experience

  • Hands-on experience with Apache Kafka, including Kafka Streams, Kafka Connect, and the development of Kafka-based integrations.
  • Experience with Apache Pulsar or Apache Storm, particularly in legacy system maintenance or modernization initiatives.
  • Practical experience with streaming and distributed processing frameworks such as Apache Flink, Apache Spark, or Spark Streaming.
  • Familiarity with Microsoft Azure services and hybrid or multi-cloud environments.
  • Solid understanding of event-driven architectures, asynchronous communication patterns, and messaging systems, including AMQP.
  • Experience processing telemetry, IoT, or other event data generated by physical devices.
Qualification wording
Hands-on experience with Apache Kafka, including Kafka Streams, Kafka Connect, and the development of Kafka-based integrations.
Experience with Apache Pulsar or Apache Storm, particularly in legacy system maintenance or modernization initiatives.
Practical experience with streaming and distributed processing frameworks such as Apache Flink, Apache Spark, or Spark Streaming.
Familiarity with Microsoft Azure services and hybrid or multi-cloud environments.
Solid understanding of event-driven architectures, asynchronous communication patterns, and messaging systems, including AMQP.
Experience processing telemetry, IoT, or other event data generated by physical devices.
Apply at Endava

Posting record

Report an error

Actively hiringFirst seen by us 10 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 26, 202610 days ago
Recorded sightings
18
Last seen by us
Nov 5, 2026

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 10

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

At Endava, jobs usually come down by about day 32.

From 11,069 similar postings that came down, and 85 of Endava’s. Coming down is not always a hire.

Endava is hiring

66 open jobs

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

  • Data Engineer hiring is picking up
  • Takes jobs down at a usual pace
  • 35% of open jobs were reposted
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
  • AWS
  • Azure
  • Docker
  • Kafka
  • Kubernetes
  • MongoDB
  • Redis
  • S3
  • Spark
Where the posting names them
- Implement streaming data processing solutions using technologies such as Apache Kafka, Apache Flink, and Apache Spark. - Develop and maintain Java-based services and integration components for processing data received from physical devices. - Implement complex data transformations, mappings, validations, and enrichments to support business and technical requirements.
- Strong professional experience in Data Engineering, with a focus on streaming data processing and distributed systems. - Advanced programming skills in Java (11+), including experience with the Spring framework. - Hands-on experience with Apache Kafka, including Kafka Streams, Kafka Connect, and the development of Kafka-based integrations.
- Experience deploying and operating containerized applications using Docker and Kubernetes. - Working knowledge of MongoDB, including collections, document structures, and Java-based data access. - Familiarity with Redis and its use in distributed applications.
- Implement and maintain MongoDB collections, data structures, and related application-level integrations, following architectural guidelines. - Develop, deploy, and maintain cloud-native services primarily on AWS, leveraging Kubernetes and managed cloud services. - Contribute to the modernization and migration of legacy data processing components toward Kafka-based streaming architectures.
- Experience developing and integrating microservices and distributed applications. - Hands-on experience with AWS cloud services, particularly S3, SQS, and EKS. - Experience deploying and operating containerized applications using Docker and Kubernetes.
- Experience with Apache Pulsar or Apache Storm, particularly in legacy system maintenance or modernization initiatives. - Familiarity with Microsoft Azure services and hybrid or multi-cloud environments. - Experience processing telemetry, IoT, or other event data generated by physical devices.
- Hands-on experience with AWS cloud services, particularly S3, SQS, and EKS. - Experience deploying and operating containerized applications using Docker and Kubernetes. - Working knowledge of MongoDB, including collections, document structures, and Java-based data access.
- Design, develop, and maintain scalable real-time and near-real-time data processing pipelines. - Implement streaming data processing solutions using technologies such as Apache Kafka, Apache Flink, and Apache Spark. - Develop and maintain Java-based services and integration components for processing data received from physical devices.
- Implement complex data transformations, mappings, validations, and enrichments to support business and technical requirements. - Build and maintain event-driven integrations using Kafka, Kafka Streams, Kafka Connect, and messaging protocols such as AMQP. - Ensure reliable data delivery to downstream consumers, applications, and storage systems.
- Develop, deploy, and maintain cloud-native services primarily on AWS, leveraging Kubernetes and managed cloud services. - Contribute to the modernization and migration of legacy data processing components toward Kafka-based streaming architectures. - Collaborate with technical leads and engineering teams to translate architectural designs into robust, production-ready implementations.
- Advanced programming skills in Java (11+), including experience with the Spring framework. - Hands-on experience with Apache Kafka, including Kafka Streams, Kafka Connect, and the development of Kafka-based integrations. - Practical experience with streaming and distributed processing frameworks such as Apache Flink, Apache Spark, or Spark Streaming.
- Knowledge of SMTP-based integrations. - Experience migrating legacy messaging and stream processing solutions to modern Kafka-based architectures. - Understanding of performance optimization, fault tolerance, monitoring, and observability in distributed streaming systems.
- Ensure reliable data delivery to downstream consumers, applications, and storage systems. - Implement and maintain MongoDB collections, data structures, and related application-level integrations, following architectural guidelines. - Develop, deploy, and maintain cloud-native services primarily on AWS, leveraging Kubernetes and managed cloud services.
- Working knowledge of MongoDB, including collections, document structures, and Java-based data access. - Familiarity with Redis and its use in distributed applications. - Experience with Git-based development workflows and CI/CD pipelines, preferably using GitLab and GitLab CI/CD.
- Hands-on experience with Apache Kafka, including Kafka Streams, Kafka Connect, and the development of Kafka-based integrations. - Practical experience with streaming and distributed processing frameworks such as Apache Flink, Apache Spark, or Spark Streaming. - Solid understanding of event-driven architectures, asynchronous communication patterns, and messaging systems, including AMQP.

Your next step

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Has Endava posted this job before?

Yes. We’ve followed 9 other Senior Data Engineer (Real-Time Data Processing & Streaming) jobs there since October 2026. All 9 are still up.

  1. BucharestStill up after 10 days, first seen Oct 26
  2. Cluj-NapocaStill up after 10 days, first seen Oct 26
  3. BrașovStill up after 10 days, first seen Oct 26
  4. TimișoaraStill up after 10 days, first seen Oct 26
  5. PiteştiStill up after 10 days, first seen Oct 26
  6. Târgu MureşStill up after 10 days, first seen Oct 26
  7. IașiStill up after 10 days, first seen Oct 26
  8. SuceavaStill up after 10 days, first seen Oct 26
  9. This jobUp 10 days so far, first seen Oct 26

Large employers often post one title for several teams, so these can be separate openings.

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.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 839, the most 1,314, and the latest week had 1,086.
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 ↗

Job Description

We are looking for an experienced Senior Data Engineer to join Endava and contribute to the design, development, and maintenance of scalable, high-performance data processing solutions.

In this role, you will focus on real-time data processing, streaming technologies, and event-driven architectures, working with complex data pipelines that ingest, transform, enrich, and distribute data from connected physical devices to downstream applications and storage systems.

You will collaborate closely with Tech Leads, software engineers, and cross-functional teams to build reliable, efficient, and maintainable data processing solutions in a cloud-native environment.

Key Responsibilities:

  • Design, develop, and maintain scalable real-time and near-real-time data processing pipelines.

  • Implement streaming data processing solutions using technologies such as Apache Kafka, Apache Flink, and Apache Spark.

  • Develop and maintain Java-based services and integration components for processing data received from physical devices.

  • Implement complex data transformations, mappings, validations, and enrichments to support business and technical requirements.

  • Build and maintain event-driven integrations using Kafka, Kafka Streams, Kafka Connect, and messaging protocols such as AMQP.

  • Ensure reliable data delivery to downstream consumers, applications, and storage systems.

  • Implement and maintain MongoDB collections, data structures, and related application-level integrations, following architectural guidelines.

  • Develop, deploy, and maintain cloud-native services primarily on AWS, leveraging Kubernetes and managed cloud services.

  • Contribute to the modernization and migration of legacy data processing components toward Kafka-based streaming architectures.

  • Collaborate with technical leads and engineering teams to translate architectural designs into robust, production-ready implementations.

  • Troubleshoot performance, reliability, and data consistency issues across distributed data processing systems.

  • Contribute to code quality, automated testing, CI/CD practices, and continuous improvement of engineering processes.

Qualifications

Required Skills and Experience:

  • Strong professional experience in Data Engineering, with a focus on streaming data processing and distributed systems.

  • Advanced programming skills in Java (11+), including experience with the Spring framework.

  • Hands-on experience with Apache Kafka, including Kafka Streams, Kafka Connect, and the development of Kafka-based integrations.

  • Practical experience with streaming and distributed processing frameworks such as Apache Flink, Apache Spark, or Spark Streaming.

  • Solid understanding of event-driven architectures, asynchronous communication patterns, and messaging systems, including AMQP.

  • Experience designing and implementing data transformation, enrichment, and integration pipelines.

  • Experience developing and integrating microservices and distributed applications.

  • Hands-on experience with AWS cloud services, particularly S3, SQS, and EKS.

  • Experience deploying and operating containerized applications using Docker and Kubernetes.

  • Working knowledge of MongoDB, including collections, document structures, and Java-based data access.

  • Familiarity with Redis and its use in distributed applications.

  • Experience with Git-based development workflows and CI/CD pipelines, preferably using GitLab and GitLab CI/CD.

  • Strong troubleshooting and problem-solving skills, particularly in distributed, high-throughput data processing environments.

  • Ability to work collaboratively with technical leads and cross-functional engineering teams, while taking ownership of implementation and delivery.

Nice to Have:

  • Experience with Apache Pulsar or Apache Storm, particularly in legacy system maintenance or modernization initiatives.

  • Familiarity with Microsoft Azure services and hybrid or multi-cloud environments.

  • Experience processing telemetry, IoT, or other event data generated by physical devices.

  • Knowledge of SMTP-based integrations.

  • Experience migrating legacy messaging and stream processing solutions to modern Kafka-based architectures.

  • Understanding of performance optimization, fault tolerance, monitoring, and observability in distributed streaming systems.

Additional Information

Discover some of the global benefits that empower our people to become the best version of themselves:

  • Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus;  
  • Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;
  • Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences;
  • Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme;
  • Health: Global internal wellbeing programme, access to wellbeing apps;
  • Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.

At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.

At Endava, we’re committed to creating an open, inclusive, and respectful environment where everyone feels safe, valued, and empowered to be their best. We welcome applications from people of all backgrounds, experiences, and perspectives—because we know that inclusive teams help us deliver smarter, more innovative solutions for our customers. Hiring decisions are based on merit, skills, qualifications, and potential. If you need adjustments or support during the recruitment process, please let us know.

Company Description

Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change.
 
By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.
 
From prototype to real-world impact - be part of a global shift by doing work that matters.

Source details

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Location & working pattern

Craiova, Dolj, Romania

- Experience with Apache Pulsar or Apache Storm, particularly in legacy system maintenance or modernization initiatives. - Familiarity with Microsoft Azure services and hybrid or multi-cloud environments. - Experience processing telemetry, IoT, or other event data generated by physical devices.
More source context
- Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences; - Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme; - Health: Global internal wellbeing programme, access to wellbeing apps;
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