• Senior Engineer 2

    House of Blues (IN)


    Job Summary:

    Job Title: Senior Data Engineer – Machine Learning & Data EngineeringLocation: Gurgaon [IND]Department: Data Engineering / Data ScienceEmployment 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.