Data Engineer (Quantexa)

NextWave Consulting Ltd; Mumbai; Remote; INR 1,000,000 - 1,500,000; Full time

Job summary

A global consulting firm is looking for a Quantexa Certified Data Engineer based in India. This hands-on role involves building and operating production-grade data pipelines, implementing solutions within the Quantexa platform, and deploying workloads on cloud environments like AWS or Azure. Ideal candidates will have 2-4 years of experience in data engineering, strong proficiency in Scala, Java, or Python, and a commitment to best engineering practices. This position plays a critical role in delivering high-impact projects for international clients.

Qualifications

• Quantexa certification is mandatory for the role.
• 2-4 years of hands-on experience in data engineering or backend/software engineering roles.
• Proficiency in Scala, Java, or Python, with a preference for Scala.
• Experience with Apache Spark and distributed data processing concepts.
• Familiarity with version control using Git and CI/CD tools.
• Understanding of testing frameworks and quality assurance.

Responsibilities

• Build and operate production-grade data pipelines.
• Implement Quantexa platform solutions in client environments.
• Deploy data workloads on cloud platforms like AWS, Azure, or GCP.
• Write maintainable code suitable for enterprise environments.
• Collaborate with technical teams for client-facing delivery.

Skills

Quantexa Certification

Scala

Java

Python

Apache Spark

Git

Docker

Tools

Gradle

Jenkins

Job description

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
  • Clear 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)