Staff Data Solutions Engineer
New
J
JobgetherData & AI
IndiaFull-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 8+ years
- Required Skills
- PythonSQLJavaC#CI/CDScalaData modeling
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related discipline.
- 8+ years of hands-on experience designing, building, and productionizing scalable data infrastructure and products.
- Ability to create and communicate HLD and LLD artifacts, including architecture diagrams, data flows, and API contracts.
- Strong architectural and problem-solving skills for translating high-level decisions into engineering specifications.
- Expert-level SQL skills and experience with large-scale distributed data systems.
- Strong software engineering expertise in testing, CI/CD, code reviews, and monitoring.
- Professional development experience in an object-oriented programming language, preferably Python (Scala, Java, or C# also relevant).
- Hands-on experience integrating AI/ML capabilities, including LLM APIs, RAG architectures, vector search, and embeddings.
- Understanding of event-driven architecture, microservices, pipeline orchestration, and layered data architecture.
- Excellent collaboration and technical influencing skills for leading without direct line-management responsibility.
- Proactive, adaptable, and continuous-learning mindset.
Responsibilities
- Design end-to-end data and AI solutions, translating architectural direction into detailed HLD and LLD specifications.
- Establish and promote strong engineering standards covering software design, testing, CI/CD, and code quality.
- Design, build, and maintain scalable data pipelines, data products, and distributed data solutions.
- Integrate AI and machine learning capabilities into production-grade applications, including LLM-based solutions and RAG architectures.
- Evaluate technology options to determine build vs. buy strategies while prioritizing scalability and cost effectiveness.
- Collaborate with cross-functional teams to ensure solutions meet enterprise standards for security, resilience, and compliance.
- Provide technical leadership and assurance across internal teams and third-party partners.
- Define reliability, SLA, observability, and operational requirements for systems under technical leadership.
- Turn ambiguous challenges into prototypes and implementation approaches using AI tools.
- Mentor engineers and contribute to knowledge sharing and engineering best practices.
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