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Lead Data Engineer

India, Noida · Job Posted April 16, 2026
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Job Description

We’re looking for a Senior/Lead Data Engineer to join our team. We are seeking a highly skilled Senior/Lead Data Engineer with 7–9 years of experience to design, build, and maintain scalable data pipelines and infrastructure. This role focuses on enabling analytics, operational reporting, and AI/ML workloads. You will collaborate closely with data analysts, data scientists, and engineering teams to ensure data availability, quality, and performance, while contributing to AI-enabled data products and ML pipeline development.

Job Responsibility

  • Design, develop, and maintain scalable ETL/ELT pipelines for processing large datasets
  • Build data pipelines to ingest, transform, and load data into data lakes, warehouses, and feature stores
  • Optimise data workflows for performance, reliability, and scalability
  • Integrate data from multiple sources, including APIs, databases, and file systems (JSON, CSV, Parquet)
  • Manage relational and non-relational databases, including columnar databases like ClickHouse
  • Ensure efficient data storage and retrieval for both analytics and ML workloads
  • Implement data quality checks, validation frameworks, and monitoring systems
  • Maintain data lineage, metadata management, and governance standards
  • Ensure data accuracy, consistency, and compliance for analytics and AI/ML use cases
  • Deploy and manage data solutions on cloud platforms (AWS, Azure, GCP) or on-prem environments
  • Work with cloud data services such as Redshift, Big Query, S3, RDS, and Azure Synapse
  • Monitor and optimise infrastructure for cost, performance, and scalability
  • Collaborate with data scientists to build and operationalise feature engineering pipelines
  • Develop and manage feature stores (e.g., Feast, Tecton)
  • Support ML pipelines for training, batch processing, and real-time inference
  • Ensure proper dataset versioning, schema management, and data validation for ML workflows
  • Understand model monitoring, metadata tracking, and data drift concepts
  • Work closely with cross-functional teams to understand business and technical requirements
  • Provide data-driven insights to support decision-making and product development
  • Contribute to building scalable, AI-driven data platforms

Requirements

  • Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field
  • 7–9 years of experience as a Data Engineer or in a similar role
  • Strong experience in building and maintaining ETL/ELT pipelines
  • Experience supporting analytics and AI/ML data workflows
  • Hands-on experience with ETL tools such as Apache Airflow, Airbyte, and dbt
  • Strong expertise in SQL and NoSQL databases (MySQL, PostgreSQL, MongoDB, Redis)
  • Proficiency in Python and Shell scripting for data processing and automation
  • Experience with cloud platforms (AWS, Azure, GCP) and their data services
  • Familiarity with data warehousing solutions such as Amazon Redshift or Snowflake
  • Experience with containerization tools like Docker and orchestration using Kubernetes
  • Understanding of CI/CD pipelines for deploying data and ML workflows
  • Experience with BI tools (Power BI preferred)
  • Strong analytical and problem-solving skills
  • Ability to manage multiple projects and priorities
  • Excellent communication and collaboration skills
  • High attention to detail and data quality
  • Ability to work in a fast-paced, evolving environment
  • Leadership & Mentorship: Guide and mentor junior engineers, promoting best practices
  • Effective Communication: Clearly articulate technical concepts to stakeholders
  • Problem-Solving Attitude: Proactively identify issues and deliver solutions
  • Collaboration & Teamwork: Work effectively across teams to achieve shared goals
  • Adaptability & Flexibility: Stay updated with emerging technologies and adapt quickly

Nice to have

  • Experience with big data technologies like Hadoop, Spark, or Kafka
  • Familiarity with machine learning pipelines and feature engineering workflows
  • Experience with columnar databases such as ClickHouse
  • Exposure to vector databases (Pinecone, Chroma, pgvector)
  • Experience working on AI/ML data platforms, feature stores, or LLM-based solutions

What we offer

  • Competitive salaries
  • Health benefits
  • Various perks
  • Competitive compensation and performance-based incentives
  • Opportunities for professional growth through workshops and certifications
  • Flexible work-life balance with remote options
  • Collaborative culture
  • Exposure to diverse projects across various industries
  • Clear career advancement pathways
  • Comprehensive health benefits
  • Perks like team-building activities

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