Lead Enterprise Data Engineer

5 days ago


Ghaziabad, Uttar Pradesh, India beBeeData Full time ₹ 30,00,000 - ₹ 40,00,000
Senior Data Architect Position

This position involves working with data scientists and architects to translate prototypes into scalable solutions. The role requires designing and building robust, scalable, and high-quality data pipelines that support analytics and reporting needs.

Key Responsibilities:
  • Designing & Developing Data Pipelines:
    • Integration of 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:
    • 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.
  • 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:
    • 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.
    • 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.

A degree is not required, as long as the candidate has the right skillset and can commit to the work/projects assigned.



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