Senior Data Engineer / ML Pipeline Specialist

This role involves designing, building, and maintaining scalable data science pipelines for ML model training, evaluation, and deployment. The specialist will collaborate with data scientists and ML engineers to translate business problems into data-driven solutions, implement and optimize machine learning models for production, and ensure data quality. Responsibilities also include automating data ingestion, transformation, and feature engineering workflows, monitoring model performance, and contributing to MLOps practices like CI/CD and model versioning. Candidates should have 6-10 years of experience in data engineering or applied machine learning, with strong proficiency in Python, SQL, distributed data processing, and cloud platforms.

Must Have

• Design, build, and maintain scalable data science pipelines for model training, evaluation, and deployment.
• Collaborate with data scientists, ML engineers, and product teams to translate business problems into data-driven solutions.
• Implement and optimize machine learning models for production environments.
• Ensure data quality, consistency, and availability across the pipeline.
• Automate data ingestion, transformation, and feature engineering workflows.
• Monitor model performance and retrain pipelines as needed to maintain accuracy.
• Contribute to MLOps practices, including CI/CD, model versioning, and governance.
• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• 6–10 years of experience in data engineering or applied machine learning roles.
• Strong experience in building and deploying ML models in production.
• Proficient in Python, SQL, and distributed data processing frameworks.
• Familiarity with cloud platforms (Azure, AWS, or GCP) and containerization tools.
• Excellent problem-solving and communication skills.

Good to Have

• Experience with Generative AI tools (LangChain, Hugging Face, Azure OpenAI).
• Exposure to vector databases and semantic search.
• Familiarity with evaluation frameworks and responsible AI practices.
• Domain knowledge in BFSI, Retail, or Healthcare.

Overseas Contractor

Job Req Id: 1419106

Senior Data Engineer / ML Pipeline Specialist

Roles & Responsibilities

• Design, build, and maintain scalable data science pipelines for model training, evaluation, and deployment.
• Collaborate with data scientists, ML engineers, and product teams to translate business problems into data-driven solutions.
• Implement and optimize machine learning models for production environments.
• Ensure data quality, consistency, and availability across the pipeline.
• Automate data ingestion, transformation, and feature engineering workflows.
• Monitor model performance and retrain pipelines as needed to maintain accuracy.
• Contribute to MLOps practices, including CI/CD, model versioning, and governance.

Experience & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• 6–10 years of experience in data engineering or applied machine learning roles.
• Strong experience in building and deploying ML models in production.
• Proficient in Python, SQL, and distributed data processing frameworks.
• Familiarity with cloud platforms (Azure, AWS, or GCP) and containerization tools.
• Excellent problem-solving and communication skills.

Primary Skills (Mandatory)

• Programming: Python, Pandas, NumPy, Scikit-learn, PySpark, SQL
• Data Engineering: Airflow, Spark, Databricks, Delta Lake
• MLOps: MLflow, DVC, Docker, Kubernetes, CI/CD pipelines
• Cloud Platforms: Azure Data Factory, AWS Glue, GCP Dataflow
• Data Stores: Snowflake, PostgreSQL, MongoDB, ChromaDB
• Model Deployment: FastAPI, Flask, RESTful APIs
• Monitoring & Logging: Prometheus, Grafana, ELK/EFK stack
• Security & Compliance: IAM, Key Vault, encryption, GDPR/SOC2

Secondary Skills (Good to Have)

• Experience with Generative AI tools (LangChain, Hugging Face, Azure OpenAI).
• Exposure to vector databases and semantic search.
• Familiarity with evaluation frameworks and responsible AI practices.
• Domain knowledge in BFSI, Retail, or Healthcare.

Min Salary:

Max Salary:

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