KJBN labs

Senior Software Engineer - Backend

A Senior Software Backend Engineer is responsible for designing, building, and maintaining the server-side

logic and infrastructure of web applications or software systems. They typically work closely with frontend

engineers, DevOps teams, and other stakeholders to ensure that the back-end services perform optimally and

meet business requirements. Below is an outline of a typical Senior Backend Developer job profile:

Key Responsibilities:

1. System Architecture & Design:

- Design scalable, high-performance backend services and APIs.

- Participate in the planning, design, and development of new features.

- Ensure that systems are designed with fault tolerance, security, and scalability in mind.

2. Development & Implementation:

- Write clean, maintainable, and efficient code.

- Implement server-side logic, databases, and data storage solutions.

- Work with technologies like REST, GraphQL, and other backend communication methods.

- Design and optimize database schemas, queries, and indexes.

3. Performance Optimization:

- Diagnose and fix performance bottlenecks.

- Optimize backend processes and database queries for speed and efficiency.

- Implement caching strategies and load balancing.

4. Security:

- Ensure the security of the backend systems by implementing secure coding practices.

- Protect against common security threats such as SQL injection, cross-site scripting (XSS), and others.

5. Collaboration & Leadership:

- Collaborate with frontend teams, product managers, and DevOps engineers.

- Mentor junior developers and guide them in best practices.

- Participate in code reviews and ensure that the development team follows consistent coding standards.

6. Testing & Debugging:

- Develop and run unit, integration, and performance tests to ensure code quality.

- Troubleshoot, debug, and upgrade existing systems.

7. Monitoring & Maintenance:

- Monitor system performance and take preventive measures to ensure uptime and reliability.

- Maintain technical documentation for reference and reporting.

- Stay updated on emerging technologies and incorporate them into the backend tech stack.

Required Skills:

1. Programming Languages:

- Expertise in one or more backend programming languages in the list Python, Java, Go, Rust.

2. Database Management:

- Strong understanding of both relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g.,

MongoDB, Redis).

- Knowledge of data modeling, query optimization, and database scaling strategies.

3. API Design & Development:

- Proficiency in designing and implementing RESTful and GraphQL APIs.

- Experience with microservices architecture.

- Good understanding of containers

4. Cloud & DevOps:

- Familiarity with cloud platforms like AWS, Azure, or Google Cloud.

- Understanding of DevOps principles, CI/CD pipelines, containerization (Docker), and orchestration

(Kubernetes).

5. Version Control:

- Proficiency with Git and branching strategies.

6. Testing & Debugging Tools:

- Familiarity with testing frameworks, debugging tools, and performance profiling.

7. Soft Skills:

- Strong problem-solving skills.

- Excellent communication and teamwork abilities.

- Leadership and mentorship qualities.

Qualifications:

- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field.

- 5+ years of experience in backend development or software engineering.

- Proven experience with system design, architecture, and high-scale application development.

Preferred Qualifications:

- Experience with distributed systems, event-driven architectures, and asynchronous processing.

- Familiarity with message queues (e.g., RabbitMQ, Kafka) and caching layers (e.g., Redis, Memcached).

- Knowledge of infrastructure as code (IaC) tools like Terraform or Ansible.

Tools & Technologies:

- Languages: Python, Java, Golang, Rust.

- Databases: PostgreSQL, MySQL, MongoDB, Redis, Cassandra.

- Frameworks: Django, Flask, Spring Boot, Go Micro.

- Cloud Providers: AWS, Azure, Google Cloud.

- Containerization: Docker, Kubernetes.

- CI/CD: Jenkins, GitLab CI, CircleCI.

This job profile will vary depending on the company and industry, but the core principles of designing,

developing, and maintaining back-end systems remain the same.

Senior Data Engineer Job Description

Overview

The Senior Data Engineer will design, develop, and maintain scalable data pipelines and

infrastructure to support data-driven decision-making and advanced analytics. This role requires deep

expertise in data engineering, strong problem-solving skills, and the ability to collaborate with

cross-functional teams to deliver robust data solutions.

Key Responsibilities

Data Pipeline Development: Design, build, and optimize scalable, secure, and reliable data

pipelines to ingest, process, and transform large volumes of structured and unstructured data.

Data Architecture: Architect and maintain data storage solutions, including data lakes, data

warehouses, and databases, ensuring performance, scalability, and cost-efficiency.

Data Integration: Integrate data from diverse sources, including APIs, third-party systems,

and streaming platforms, ensuring data quality and consistency.

Performance Optimization: Monitor and optimize data systems for performance, scalability,

and cost, implementing best practices for partitioning, indexing, and caching.

Collaboration: Work closely with data scientists, analysts, and software engineers to

understand data needs and deliver solutions that enable advanced analytics, machine

learning, and reporting.

Data Governance: Implement data governance policies, ensuring compliance with data

security, privacy regulations (e.g., GDPR, CCPA), and internal standards.

Automation: Develop automated processes for data ingestion, transformation, and validation

to improve efficiency and reduce manual intervention.

Mentorship: Guide and mentor junior data engineers, fostering a culture of technical

excellence and continuous learning.

Troubleshooting: Diagnose and resolve complex data-related issues, ensuring high

availability and reliability of data systems.

Required Qualifications

Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science,

or a related field.

Experience: 5+ years of experience in data engineering or a related role, with a proven track

record of building scalable data pipelines and infrastructure.

Technical Skills:

Proficiency in programming languages such as Python, Java, or Scala.

Expertise in SQL and experience with NoSQL databases (e.g., MongoDB, Cassandra).

Strong experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services

(e.g., Redshift, BigQuery, Snowflake).

Hands-on experience with ETL/ELT tools (e.g., Apache Airflow, Talend, Informatica) and

data integration frameworks.

Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka) and distributed

systems.

Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) is a

plus.

Soft Skills:

Excellent problem-solving and analytical skills.

Strong communication and collaboration abilities.

Ability to work in a fast-paced, dynamic environment and manage multiple priorities.

Certifications (optional but preferred): Cloud certifications (e.g., AWS Certified Data Analytics,

Google Professional Data Engineer) or relevant data engineering certifications.

Preferred Qualifica

Experience with real-time data processing and streaming architectures.

Familiarity with machine learning pipelines and MLOps practices.

Knowledge of data visualization tools (e.g., Tableau, Power BI) and their integration with data

pipelines.

Experience in industries with high data complexity, such as finance, healthcare, or

e-commerce.

Work Environment

Location: Hybrid/Remote/On-site (depending on company policy).

Team: Collaborative, cross-functional team environment with data scientists, analysts, and

business stakeholders.

Hours: Full-time, with occasional on-call responsibilities for critical data systems.