Senior Engineer 2

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.