Lead Data Architect

5 days ago

Thāne, Maharashtra, India beBeeCloud Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

**Senior Data Engineer Role**

  • Design and build robust, scalable data pipelines that support analytics and reporting needs.

As a Senior Data Engineer, you will collaborate with cross-functional teams to translate requirements into technical solutions. This includes working closely with product owners, architects, and business stakeholders to develop enterprise data analytics solutions from source systems through ingestion and reporting.

Key Responsibilities:

  • Develop and deploy scalable ETL/ELT pipelines for batch and streaming data using Azure Data Factory, Databricks, Snowflake, and Azure SQL Server.
  • Collaborate with data scientists, analysts, and platform engineers to enable analytics and machine learning use cases.
  • Design, develop, and optimize DBT models to support scalable data transformations.
  • 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.
  • Ensure data integrity, privacy, and compliance through governance practices and secure schema design.
  • Implement data masking, access controls, and metadata management for sensitive datasets.

Required Skills:

  • 7+ years of data engineering or design experience designing, developing, and deploying scalable enterprise data analytics solutions.
  • 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).
  • Experience with CI/CD tools such as GitHub Actions, GitLab, Jenkins, or similar tools.
  • Proficiency in SQL and any one other programming language (e.g., R, Python, C++, Minitab, SAS, Matlab, VBA).

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