Why This Role Matters

As a Quantexa Certified Data Engineer, you will sit at the core of complex, high-impact delivery programmes for global clients across financial crime, fraud, risk, and customer intelligence.
Your work will directly influence how large-scale data is ingested, modelled, engineered, and operationalised on the Quantexa platform in production environments.

This is a hands-on engineering role for practitioners who have already worked on real data pipelines and want to operate at enterprise scale.

What You Will Do

1. Build & Operate Production-Grade Data Pipelines

- Design, engineer, and maintain robust batch and streaming data pipelines for high-volume, high-velocity data.
- Ensure pipelines are fault-tolerant, performant, and production-ready.

2. Implement Quantexa Platform Solutions

- Configure and deploy Quantexa solutions in client environments.
- Work with distributed data processing frameworks (Spark, Hadoop) and search/indexing technologies (e.g., Elasticsearch) as part of Quantexa deployments.
- Support data ingestion, transformation, and enrichment aligned to Quantexa data models.

3. Cloud-Native Delivery

- Deploy and operate data workloads on one or more cloud platforms: AWS, Azure, or GCP.
- Contribute to infrastructure and environment setup in collaboration with DevOps / platform teams.

4. Engineering Excellence

- Write clean, defensive, maintainable code suitable for enterprise production environments.
- Apply engineering best practices for logging, error handling, performance optimisation, and monitoring.

5. Client-Facing Technical Delivery

- Work closely with Solution Architects, Delivery Leads, and client engineering teams.
- Translate technical design into executable data engineering solutions.
- Support technical discussions with client-side engineers and data teams.

6.



Collaboration & Knowledge Sharing

- Contribute to internal standards, reusable patterns, and documentation.
- Share learnings and best practices within delivery teams.

What You Must Bring (Non-Negotiable)

- Quantexa Certification – Mandatory
- Candidates must hold an active Quantexa certification relevant to data engineering or platform delivery.

- Experience

- 2–4 years of hands-on experience in data engineering or backend/software engineering roles.
- Proven experience building and operating data pipelines in production environments.

- Programming

- Strong proficiency in Scala, Java, or Python (Scala preferred in Quantexa delivery environments).
- Solid understanding of software engineering fundamentals beyond just scripting.

- Big Data & Distributed Systems

- Practical experience with Apache Spark and distributed data processing concepts.
- Understanding of data ingestion, transformation, and large-scale data processing patterns.

- DevOps & Engineering Tooling

- Hands-on experience with:
- Git (version control)
- Build and CI/CD tools (e.g., Gradle, Jenkins)
- Containers (Docker)
- Linux/Bash scripting

- Testing & Quality

- Transparent understanding of unit vs integration testing.
- Experience using testing frameworks (e.g., ScalaTest or equivalent).

- Professional Communication

- Ability to work in client delivery environments and communicate technical concepts clearly to both technical and non-technical stakeholders.

Good to Have (Value Add, Not Mandatory)

- Prior experience working in domains such as financial services, risk, compliance, fraud, or AML.
- Experience mentoring junior engineers or contributing to team onboarding.
- Exposure to performance tuning, data quality frameworks, or large-scale data migrations.

Location

India (Delivery roles aligned to global client projects)

📌 Data Engineer (Quantexa) (Maharashtra)
🏢 Important Business
📍 Maharashtra