Highly Skilled Data Engineer

5 days ago

Vadodara, Gujarat, India beBeeDataEngineer Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Senior Data Engineering Role

As a key member of the data engineering team, you will be responsible for designing and building robust, scalable, and high-quality data pipelines that support analytics and reporting needs.

Key Responsibilities:
  1. Data Pipeline Design & Development:
  • 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.
  • Collaborate with data scientists, analysts, and platform engineers to enable analytics and ML use cases.
  • Design, develop, and optimize DBT models to support scalable data transformations.
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.

Required Skills & Qualifications:

  • 7+ years of experience in 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.
  • 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.
  • 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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