Senior Big Data Architect

8 hours ago

Bharatpur, Rajasthan, India beBeeDataEngineer Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Job Description

As a senior data engineer, you will play a pivotal role in designing and building scalable, robust, and high-quality data pipelines that support analytics and reporting needs.

You will work closely with data scientists and architects to translate prototypes into scalable solutions, utilizing your skills in cloud platforms, data tools, and governance practices.

  • Data Pipeline Design & Development

Key responsibilities include:

  • Designing and developing complex data pipelines that integrate structured and unstructured data from various sources into data lakes and warehouses.
  • Building and maintaining scalable ETL/ELT pipelines for batch and streaming data using Azure Data Factory, Databricks, Snowflake, and Azure SQL Server.
  • Collaborating with data scientists, analysts, and platform engineers to enable analytics and ML use cases.
  • Designing, developing, and optimizing DBT models to support scalable data transformations.
  • Cloud Platform Engineering

Operationalizing data solutions on cloud platforms, integrating services like Azure, Snowflake, and third-party technologies.

  • Managing environments, performance tuning, and configuration for cloud-native data solutions.
  • Data Modeling & Architecture

Applying dimensional modeling, star schemas, and data warehousing techniques to support business intelligence and machine learning workflows.

  • Collaborating with solution architects and analysts to ensure models meet business needs.
  • Data Governance & Security

Ensuring data integrity, privacy, and compliance through governance practices and secure schema design.

  • Implementing data masking, access controls, and metadata management for sensitive datasets.
  • Collaboration & Agile Delivery

Working closely with cross-functional teams including product owners, architects, and business stakeholders to translate requirements into technical solutions.

  • Participating in Agile ceremonies, sprint planning, and DevOps practices for continuous integration and deployment.
Required Skills and Qualifications

To be successful in this role, you will need:

  • At least 7 years of experience in data engineering or design.
  • 5+ years of experience in ML Lifecycle using Azure Kubernetes service, Azure Container Instance service, Azure Data Factory, Azure Monitor, Azure DataBricks.
  • 5+ years of experience in data engineering using Snowflake.
  • Experience in designing, developing, and scaling complex data and 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.
  • 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.

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