Roles and responsibilities - Tredence is looking for a Data Engineer to design, build, and scale high-performance data platforms and pipelines. The ideal candidate will have strong expertise in Spark, Scala + GCP cloud, with experience leading engineering teams and delivering enterprise-grade data solutions. Exposure to any cloud platform is a plus.

Key Responsibilities

- Lead the design and development of scalable, fault-tolerant data pipelines and streaming architectures.

- Build and maintain real-time and batch data processing systems using Kafka, Spark, and Scala.

- Architect large-scale data solutions ensuring performance, reliability, and security.

- Collaborate with data scientists, analysts, and business stakeholders to deliver data-driven solutions.

- Mentor and guide junior engineers; drive best practices in coding, design, and deployment.

- Optimize data workflows and improve system efficiency and scalability.

- Implement monitoring, logging,



and alerting mechanisms for data platforms.

- Drive adoption of up-to-date data engineering practices (CI/CD, data quality frameworks, etc.).

Mandatory SkillsStrong hands-on experience with:o Apache Kafka (streaming, producers/consumers, topic management)o Apache Spark (batch & streaming)o Scala (advanced programming expertise)Solid understanding of data engineering concepts, distributed systems, and big data architecturesExperience working with large-scale data processing and pipeline development.Excellent comm skillsStrong problem-solving and leadership skills.Good to Have (Optional Skills)Experience with any cloud platform: AWS / Azure / GCPKnowledge of data lakes, lakehouse architectures (Delta Lake, Iceberg, etc.)Familiarity with containerization tools (Docker, Kubernetes)Experience with orchestration tools (Airflow, etc.)

📌 Data Engineer - Bangalore (Bengaluru)
🏢 Quess
📍 Bengaluru