Senior Enterprise Data Architect

2 weeks ago


Davangere, Karnataka, India beBeeDataEngineering Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Overview

This role is for a seasoned Data Engineering professional with a focus on designing, developing and deploying scalable enterprise data analytics solutions.

The ideal candidate will have extensive experience in data engineering using Snowflake, as well as expertise in cloud platforms and containerization technologies.

  • Data Pipeline Design & Development
    • Design and build robust, scalable, and high-quality data pipelines that support analytics and reporting needs.
    • Integrate structured and unstructured data from various sources into data lakes and warehouses.
    • Build and maintain scalable ETL/ELT pipelines for batch and streaming data using Azure Data Factory, Databricks, Snowflake, and Azure SQL Server.
  • Cloud Platform Engineering
    • Operationalize data solutions on cloud platforms, integrating services like Azure, Snowflake, and third-party technologies.
    • Manage environments, performance tuning, and configuration for cloud-native data solutions.
  • Data Modeling & Architecture
    • Apply dimensional modeling, star schemas, and data warehousing techniques to support business intelligence and machine learning workflows.
    • Collaborate with solution architects and analysts to ensure models meet business needs.
  • Data Governance & Security
    • Ensure data integrity, privacy, and compliance through governance practices and secure schema design.
    • Implement data masking, access controls, and metadata management for sensitive datasets.
  • Collaboration & Agile Delivery
    • Work closely with cross-functional teams including product owners, architects, and business stakeholders to translate requirements into technical solutions.
    • Participate in Agile ceremonies, sprint planning, and DevOps practices for continuous integration and deployment.
Key Requirements
  • A minimum of 7 years of experience in data engineering or design, with a focus on designing, developing and deploying scalable enterprise data analytics solutions.
  • At least 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.
  • Experience in designing, developing & scaling complex data & feature pipelines feeding ML models and evaluating their performance.
  • Strong experience with cloud platforms (AWS, Azure, etc.) and containerization technologies (Docker, Kubernetes).
  • Proficiency in SQL and any one other programming language (e.g., R, Python, C++, Minitab, SAS, Matlab, VBA).
About the Role

This is an exciting opportunity to join a team of experienced professionals who are passionate about delivering innovative data solutions. If you're looking for a challenging role that will push your skills to the next level, this could be the perfect fit for you.



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