Jobgether
Senior Software Engineer, Backend - Data Streaming
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Job Description: Senior Software Engineer, Backend - Data Streaming
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer, Backend - Data Streaming based in United Kingdom.
This is a foundational backend engineering role focused on building a new data streaming architecture from the ground up.
You will help create a durable, continuously written streaming layer that separates data consumption from a live process execution engine.
The role combines distributed systems, event streaming, cloud storage, and large-scale data architecture.
You will shape core architectural decisions around consistency, durability, scalability, and reliable data delivery.
Working within a small, high-ownership team, you will have significant influence over both the technology and the evolution of the team’s scope.
You will also collaborate closely with Product, Data Layer, Distributed Systems, QA, Support, and SRE teams in a remote-first environment.
This is an opportunity to work on greenfield infrastructure with direct impact on how customers access and use process data at scale.
Accountabilities
- Design and build the core streaming infrastructure that decouples process data access from the live execution engine, using durable and cost-efficient storage.
- Develop customer-facing data streaming capabilities that enable reliable integration with platforms such as Kafka and allow customers to consume process data within their own systems.
- Help redesign how analytics products consume and serve process data at scale, moving data access away from the engine’s critical path.
- Make foundational architectural decisions within a small, high-ownership team, particularly around consistency, durability, distributed streaming pipelines, and data reliability.
- Lead medium-to-large engineering initiatives from solution design and planning through cross-team coordination and predictable delivery.
- Work closely with Product to translate requirements into actionable technical solutions and help shape the evolution of the data streaming architecture.
- Collaborate with Data Layer, Distributed Systems, QA, Support, and SRE teams to deliver reliable and scalable solutions.
- Participate in L3 support and on-call rotations, investigating production issues in the data layer and incorporating operational learnings into future product improvements.
- Contribute to clear engineering practices through code reviews, technical discussions, direct feedback, and collaborative problem-solving.
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Requirements:
- 7+ years of backend engineering experience, with strong expertise in Java and a focus on distributed or data-intensive systems.
- Hands-on experience with object storage technologies such as S3, GCS, Azure, or similar, including experience designing reliable and idempotent upload and commit protocols.
- Practical experience with Kafka or comparable streaming and event-log technologies.
- Strong understanding of distributed systems fundamentals, including consistency, durability, scalability, and fault-tolerant data processing.
- Demonstrated ability to drive technical initiatives through ambiguity and help design systems that are still evolving, rather than only extending established architectures.
- Proven experience leading engineering initiatives lasting three months or more, covering solution design, project planning, cross-team coordination, and delivery.
- Strong communication and collaboration skills, with the ability to work effectively in a remote-first environment and communicate technical concepts clearly with both technical and product stakeholders.
- Comfortable providing and receiving direct, constructive feedback through code reviews and technical collaboration.
- Willingness and ability to use the product as part of understanding the systems and customer experience.
- Experience with Apache Iceberg, Parquet, or broader lakehouse and data-lake architectures is a plus.
- Familiarity with embedded state stores such as RocksDB for projection or checkpointing workloads is desirable.
- Experience with stream-processing frameworks such as Apache Flink, particularly stateful processing and checkpointing, is an advantage.
- Familiarity with object-storage-native streaming architectures is beneficial.
Benefits:
- Fully remote and globally distributed work environment.
- Flexible work arrangements designed to support different locations and working styles.
- Home office budget and co-working space support.
- Flexible time off to recharge and maintain sustainable work-life balance.
- Annual company-wide kickoff, team offsites, local gatherings, and connection budgets to support meaningful in-person collaboration.
- Locally tailored healthcare benefits where applicable.
- Access to Modern Health for global mental wellbeing support.
- Live Well Lifestyle Spending Account supporting fitness, family care, personal interests, experiences, and financial wellbeing, scaling to €1,000 annually from 2027.
- Retirement and pension plans, often including company contributions, plus life and disability insurance where applicable.
- Up to $1,000 / €1,000 / £1,000 per year for self-directed professional development, including courses, certifications, and books.
- Opportunity to work on greenfield distributed systems and highly visible technical architecture.
- Significant autonomy and ownership within a small engineering team.
- Exposure to complex data streaming, analytics, and enterprise-scale infrastructure challenges.
- Compensation is location-based and varies according to market, skills, experience, and location. For employees based outside the listed compensation markets, a personalized total rewards assessment is provided during the hiring process.
- Equity may be offered through a virtual stock option plan, where applicable.
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How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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