Senior Enterprise Data Solutions Architect

2 days ago

Bellary, Karnataka, India beBeeData Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Description

The Senior Data Engineer will collaborate with Data Scientists and Architects to translate prototypes into scalable solutions.

Key Responsibilities:
  1. Data Pipeline Design & Development
  • Design and build robust, scalable, and high-quality data pipelines that support analytics and reporting needs by integrating 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 through effective data transformations.
  • Design, develop, and optimize DBT models to support scalable data transformations and ensure business intelligence and machine learning workflows meet expectations.
  1. Cloud Platform Engineering
  • Operationalize data solutions on cloud platforms, integrating services like Azure, Snowflake, and third-party technologies to drive scalability and efficiency.
  • Manage environments, performance tuning, and configuration for cloud-native data solutions to ensure seamless execution.
  1. 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 and are well-integrated.
  1. Data Governance & Security
  • Ensure data integrity, privacy, and compliance through governance practices and secure schema design to safeguard sensitive datasets.
  • Implement data masking, access controls, and metadata management for sensitive datasets to maintain confidentiality.
  1. Collaboration & Agile Delivery
  • Work closely with cross-functional teams including product owners, architects, and business stakeholders to translate requirements into technical solutions and deliver projects efficiently.
  • Participate in Agile ceremonies, sprint planning, and DevOps practices for continuous integration and deployment.
Required Skills & Qualifications
  • 7+ years of experience designing, developing, and deploying scalable enterprise data analytics solutions with a strong focus on 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 building datasets, ML pipelines, experiments, logging, and monitoring.
  • 5+ years of experience in data engineering using Snowflake to drive scalability and efficiency.
  • 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 to drive data-driven decision making.
  • 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 to ensure robust data governance.
  • Experience in developing and maintaining APIs (e.g.: REST)
  • Agile/Scrum operating experience using Azure DevOps to streamline project delivery.
  • Experience with MS Cloud - ML Azure Databricks, Data Factory, Synapse, among others.

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