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Senior Engineer 2

5 years

0 Lacs

Posted:17 hours ago| Platform: GlassDoor logo

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Job Type

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Job Description

Job Summary:

Job Title: Senior Data Engineer – Machine Learning & Data Engineering

Location: Gurgaon [IND]

Department: Data Engineering / Data Science

Employment Type: Full-Time

YoE: 5-10

About the Role:

We are looking for a Senior Data Engineer with a strong background in machine learning infrastructure , data pipeline development , and collaboration with data scientists to drive the deployment and scalability of advanced analytics and AI solutions. You will play a pivotal role in building and optimizing data systems that power ML models, dashboards, and strategic insights across the company.

Key Responsibilities:

  • Design, develop, and optimize scalable data pipelines and ETL/ELT processes to support ML workflows and analytics.
  • Collaborate with data scientists to operationalize machine learning models in production environments (batch, real-time).
  • Build and maintain data lakes, data warehouses, and feature stores using modern cloud technologies (e.g., AWS/GCP/Azure, Snowflake, Databricks).
  • Implement and maintain ML infrastructure, including model versioning, CI/CD for ML, and monitoring tools (MLflow, Airflow, Kubeflow, etc.).
  • Develop and enforce data quality, governance, and security standards.
  • Troubleshoot data issues and support the lifecycle of model development to deployment.
  • Partner with software engineers and DevOps teams to ensure data systems are robust, scalable, and secure.
  • Mentor junior engineers and provide technical leadership on data and ML infrastructure.

Qualifications:

Required:

  • 5+ years of experience in data engineering, ML infrastructure, or a related field.
  • Proficient in Python, SQL, and big data processing frameworks (Spark, Flink, or similar).
  • Experience with orchestration tools like Apache Airflow, Prefect, or Luigi.
  • Hands-on experience deploying and managing machine learning models in production.
  • Deep knowledge of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
  • Familiarity with CI/CD tools for data and ML pipelines.
  • Experience with version control, testing, and reproducibility in data workflows.

Preferred:

  • Experience with feature stores (e.g., Feast), ML experiment tracking (e.g., MLflow), and monitoring solutions.
  • Background in supporting NLP, computer vision, or time-series ML models.
  • Strong communication skills and ability to work cross-functionally with data scientists, analysts, and engineers.
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.

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