Remote Java Data Engineer
Description
Remote Java Data Engineer
Take the Lead in Building Data-Driven Futures
Are you passionate about transforming complex data into meaningful solutions that drive real-world outcomes?
Do you thrive in a collaborative remote setting where creative problem-solving and forward-thinking are part of everyday life?
If you’re ready to shape the backbone of global platforms using the latest in Java engineering and cloud architecture, this role is designed for you.
Join a pioneering team that believes the most innovative work doesn’t have borders. Here, your expertise in data pipelines, distributed computing, and modern frameworks will inform the decisions of industry leaders worldwide.
As a Remote Java Data Engineer, your vision will not only solve today’s toughest challenges but also set the standard for what’s possible tomorrow.
What Sets This Role Apart
- $85,000 Annual Salary – Your skills are valued and rewarded with a competitive compensation package.
- Fully Remote, Global Reach – Collaborate with engineers, analysts, and architects worldwide—your impact will be felt far beyond your home office.
- High-Impact Projects – Engineer data solutions for cutting-edge products serving millions.
- Modern Tool Stack – Work daily with technologies like Apache Kafka, Spark, Spring Boot, Docker, and NoSQL databases.
- Continuous Learning – Upskill with access to premium courses and live mentorship sessions tailored to the latest in machine learning and big data.
The Impact You’ll Make
Every line of code you write will help turn raw information into strategic insights.
You’ll optimize and automate data flows, design resilient APIs, and enhance real-time analytics for platforms supporting businesses worldwide.
Over the past year, our data engineering teams have improved processing speeds by 40%, accelerated go-to-market launches, and directly contributed to a 20% increase in client satisfaction ratings.
Core Responsibilities
Architect, Scalable Data Solutions
- Build, optimize, and maintain robust ETL pipelines with Java, ensuring smooth data movement and transformation across distributed systems.
- Design RESTful APIs and integrate with third-party data providers for seamless platform interoperability.
- Leverage message queues (Kafka, RabbitMQ) and microservices to enable event-driven architectures.
Drive Data Quality and Performance
- Monitor, troubleshoot, and enhance data models and storage systems—think DynamoDB, MongoDB, and PostgreSQL.
- Implement data validation, quality assurance, and error-handling frameworks that reduce downtime and maintain trust.
- Collaborate with data scientists and business intelligence teams to deliver actionable insights using advanced analytics.
Innovate and Automate
- Pioneer new tools for process automation, minimizing manual touchpoints.
- Advocate for test-driven development, code reviews, and continuous integration (Jenkins, GitHub Actions) to ensure codebase stability and transparency.
- Identify opportunities to leverage machine learning APIs or cloud-native functions to create more intelligent, more adaptable workflows.
Tech Stack & Tools
- Programming: Java 11+, Scala (bonus), Python (for scripting/automation)
- Frameworks: Spring Boot, Apache Spark, Hibernate, Micronaut
- Cloud: AWS (EC2, S3, Lambda), Azure, or Google Cloud Platform
- Data Platforms: Apache Kafka, Elasticsearch, NoSQL (MongoDB, DynamoDB), PostgreSQL
- Containerization: Docker and Kubernetes for orchestration
- CI/CD: Jenkins, GitHub Actions
- Version Control: Git
- Monitoring: Prometheus, Grafana
Work Environment & Culture
Remote doesn’t mean isolated.
Step into a dynamic, tech-forward culture where:
- Agile methodologies power transparent, two-week sprints.
- Stand-ups and sprint reviews foster collaboration across time zones.
- Knowledge-sharing sessions and hackathons are regular events on the calendar.
- Inclusion, equity, and respect are core values that drive every interaction.
You’ll have the freedom to experiment, propose new solutions, and take ownership of your projects.
The results? Rapid career progression, proper work-life balance, and a chance to make meaningful contributions—every single day.
Qualifications & Skills
Must-Have Experience
- 3+ years in Java software development with a strong focus on backend or data engineering roles.
- Hands-on expertise in building, deploying, and maintaining distributed data systems.
- Proficiency in developing APIs and microservices using modern Java frameworks.
- Familiarity with event streaming platforms such as Kafka or RabbitMQ.
- Advanced knowledge of SQL and NoSQL databases, data modeling, and performance optimization.
- Solid grasp of containerization, CI/CD, and version control best practices.
- Strong analytical mindset with a proven record of solving complex technical problems.
Preferred, but Not Required
- Experience with Apache Spark, Flink, or Hadoop.
- Exposure to cloud-native functions (AWS Lambda, GCP Functions, or Azure Functions).
- Familiarity with security best practices and data compliance standards (GDPR, HIPAA, etc.).
- Passion for learning new tools and frameworks in the rapidly evolving data engineering landscape.
Growth Opportunities & Perks
- Career Advancement: Move into senior engineering, data architect, or team lead roles as you grow.
- Learning Budget: Dedicated annual budget for courses, certifications, and conferences.
- Home Office Setup: Receive a subsidy to equip your workspace for maximum comfort and productivity.
- Wellness Initiatives: Flexible hours, health stipends, and regular team challenges for mental and physical well-being.
- Recognition: Performance-based bonuses and spot awards for breakthrough contributions.
Ready to Power the Next Era of Data Engineering?
Make your mark in a global team where your work matters—and your ideas shape the future.
This isn’t just another remote job. It’s your opportunity to architect the infrastructure that powers world-changing innovation, all while enjoying the flexibility and autonomy you deserve.
Apply now and let your data engineering journey reach new heights—no commute required. Take charge of your career from anywhere!
Frequently asked questions (FAQs)
1. What’s a regular workday like for a Java Data Engineer here?
Most mornings start with a team check-in, then it’s straight into building or tweaking data pipelines. You’ll move between writing code for ETL processes, setting up APIs, and testing new integrations. There are always a few creative problems to solve—perhaps optimizing a slow data job or finding a more efficient way to transfer information between systems. Expect to jump between solo focus time and group brainstorming with data scientists or engineers.
2. What tech stack and tools will I use most often?
You’ll write a lot of Java, often using Spring Boot for APIs and data services. Projects use Apache Kafka and RabbitMQ for event-driven work, and you’ll build with Docker and Kubernetes to keep everything scalable. For storage and analytics, you’ll get hands-on with PostgreSQL, DynamoDB, MongoDB, and sometimes Spark. Code gets shipped through CI/CD tools like Jenkins or GitHub Actions, and you’ll monitor everything with dashboards in Prometheus or Grafana.
3. How much teamwork is involved in this remote role?
Plenty! Even though you’re remote, you’ll regularly swap ideas with teammates—think daily stand-ups, sprint reviews, or jumping into a chat to tackle a bug together. Projects often mean collaborating with analysts, architects, or business intelligence teams, so you’re always learning from people with different skills and perspectives.
4. What kind of challenges will I tackle as a Java Data Engineer?
Some days you’re untangling a complex data pipeline; other days, you’re making sure data gets from A to B without a hitch. You’ll look for ways to speed up processing, keep data quality high, and find clever solutions to unusual problems—sometimes under tight deadlines or with large, fast-moving data sets. It’s a role for creative thinkers who don’t mind rolling up their sleeves.
5. Where can this job take me if I want to grow?
There’s no shortage of room to move up or branch out. If you’re curious, you could work toward becoming a lead engineer, data architect, or even step into roles that shape data strategy company-wide. The team supports upskilling—through courses, mentorship, or hands-on experience with new technology—so you can build your path as you progress.
