Senior Data Engineer

We are looking for a highly experienced Senior Data Engineer to design, build, and scale data-driven systems that power advanced analytics, machine learning models, and critical business decisioning.

This role combines hands-on engineering, technical leadership, and architectural ownership across modern data and ML ecosystems. You will collaborate closely with cross-functional teams and drive best practices in data engineering, cloud architecture, and MLOps.

Key Responsibilities

1. Lead Engineering Delivery . Build, optimize, and maintain large-scale data pipelines, batch/streaming workflows, and distributed data systems. . Lead design reviews, coding standards, and best practices for scalable data applications. . Own end-to-end delivery of data engineering components, ensuring high performance and reliability.

2. Architecture & Technology Direction . Define the technical roadmap for data engineering and MLOps capabilities. . Evaluate modern big data, cloud, and ML tools to drive innovation and adoption. . Ensure solutions follow strong architectural principles and are built for scale.

3. ML & MLOps Integration . Work closely with data scientists to productionize ML models. . Build CI/CD pipelines for ML workflows, model monitoring, and automated retraining processes. . Implement cloud-native ML infrastructure and orchestration frameworks. 4. Collaboration & Stakeholder Partnership . Work with business, analytics, and IT teams to translate business requirements into scalable engineering solutions. . Communicate complex concepts clearly to both technical and non-technical audiences.

5. Governance, Security & Quality . Ensure compliance with data governance, security guidelines, and audit requirements. . Proactively identify risks and design mitigations in architecture and delivery. . Maintain high standards of documentation, testing, and code quality. Required Skills & Qualifications (Must Have) Core Software Engineering .

• 10+ years experience coding in Java or Scala (strong backend engineering foundation). . Deep understanding of distributed systems, concurrency, performance optimization, and high-throughput data processing. Big Data & Distributed Processing (5+ years) Hands-on experience with: .
• Apache Spark (mandatory) . Hadoop ecosystem . Snowflake . AWS Glue / EMR . Azure Databricks / ADF Cloud Platforms (AWS or Azure) . Strong understanding of cloud-native architectures, data storage layers, messaging, networking, and scalability design patterns. . Experience deploying workloads in either AWS or Azure. MLOps & ML Lifecycle . Understanding of: Backend & Front-End Exposure .
• Backend frameworks: Spring Boot, Flask, FastAPI, Node.js . Front-end familiarity: React or Angular (basic awareness acceptable) Soft Skills . Excellent communication skills, with the ability to simplify and explain complex concepts. . Ability to lead by example, mentor peers, and influence engineering direction. Education . Bachelor's degree in Computer Science, Engineering, or related field (Master's/PhD preferred). Nice to Have .
• Experience with AWS SageMaker or similar ML deployment platforms . Experience deploying or tuning Large Language Models (LLMs) . Full-stack development experience . Cloud or data engineering certifications

• Apache Spark
• Data Engineering
• Hadoop Hive
• Scala
• Snowflake