Senior Analytics Developer

16 hours ago

Bharatpur, Rajasthan, India beBeeDataEngineer Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
About the Role

This is a 100% remote position that requires individuals who can work US core business hours.

  • Data Engineers are responsible for designing and building robust, scalable, and high-quality data pipelines that support analytics and reporting needs.
  • The ideal candidate will have experience in data engineering using Snowflake, Azure Data Factory, and Databricks.
  • They will also have proficiency in SQL and any one other programming language (e.g., R, Python, C++, Minitab, SAS, Matlab, VBA).
  • Strong experience with cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes) is also required.
Key Responsibilities
  • Data Pipeline Design & Development
  • Cloud Platform Engineering
  • Data Modeling & Architecture
  • Data Governance & Security
  • Collaboration & Agile Delivery
Technical Skills and Qualifications
  • 7+ years of data engineering or design experience, designing, developing, and deploying scalable enterprise data analytics solutions from source system through ingestion and reporting.
  • 5+ years of experience in ML Lifecycle using Azure Kubernetes service, Azure Container Instance service, Azure Data Factory, Azure Monitor, Azure DataBricks building datasets, ML pipelines, experiments, logging, and monitoring.
  • 5+ years of experience in data engineering using Snowflake.
  • Experience in designing, developing & scaling complex data & feature pipelines feeding ML models and evaluating their performance.
  • Experience in building and managing streaming and batch inferencing.
  • Proficiency in SQL and any one other programming language (e.g., R, Python, C++, Minitab, SAS, Matlab, VBA).
  • Strong experience with cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes).
  • Experience with CI/CD tools such as GitHub Actions, GitLab, Jenkins, or similar tools.
  • Familiarity with security best practices in DevOps and ML Ops.
  • Experience in developing and maintaining APIs (e.g.: REST)
  • Agile/Scrum operating experience using Azure DevOps.
  • Experience with MS Cloud - ML Azure Databricks, Data Factory, Synapse, among others.
Professional Skills
  • Strong analytical and problem-solving skills and passion for product development.
  • Strong understanding of Agile methodologies and open to working in agile environments with multiple stakeholders.
  • Professional attitude and service orientation; team player.
  • Ability to translate business needs into potential analytics solutions.
  • Strong work ethic: ability to work at an abstract level and gain consensus.
  • Ability to build a sense of trust and rapport to create a comfortable and effective workplace.

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