Data Engineer

About the Role
We are seeking a skilled and motivated Data Engineer (AI/ML) to design, build, and maintain scalable data pipelines and infrastructure that power advanced analytics, machine learning, and AI solutions. This role requires strong expertise in data engineering, cloud technologies, and ML operations to enable data scientists and AI teams to deliver high-impact models into production.

Key Responsibilities

• Design, develop, and maintain data pipelines for structured and unstructured data from multiple sources.

• Build and optimize data lakes, warehouses, and real-time streaming systems to support AI/ML use cases.

• Collaborate with data scientists to prepare, clean, and transform datasets for training and inference.

• Implement CI/CD pipelines and MLOps practices for model deployment, monitoring, and retraining.

• Ensure data quality, governance, and security across platforms.

• Optimize storage, compute, and processing for scalability and performance.

• Support advanced analytics, dashboards, and AI-driven applications through efficient data delivery.

Qualifications

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related field.

• 3–6 years of experience in data engineering, with exposure to AI/ML workflows.

• Strong proficiency in Python, SQL, and data processing frameworks (e.g., Spark, Beam, Hadoop).

• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and their data/AI services.

• Familiarity with machine learning lifecycle, including feature engineering, model deployment, and monitoring.

• Experience with workflow orchestration tools (e.g., Airflow, Luigi, Prefect).

• Knowledge of CI/CD, Docker, and Kubernetes for productionizing ML systems.

• Excellent problem-solving skills and ability to work in cross-functional teams.

Preferred Skills

• Experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).

• Knowledge of real-time data streaming (Kafka, Kinesis, or Pub/Sub).

• Exposure to data science frameworks (scikit-learn, TensorFlow, PyTorch) for model integration.

• Relevant certifications (e.g., AWS Big Data Specialty, GCP Data Engineer, Azure Data Engineer Associate).