Overseas Contractor

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.