Visionary Data Solutions Architect

5 days ago

Chennai Gurgaon Gurugram Bengaluru Bangalore, India beBeeDataEngineer Full time ₹ 1,04,000 - ₹ 13,08,780
Senior Data Engineer Position

We are seeking an accomplished professional to fill the role of Senior Data Engineer. The ideal candidate will be responsible for designing, implementing, and maintaining sophisticated software solutions using their expertise in Python, PySpark, SQL, and API integration on Azure platform services.

The successful candidate will be part of a team that works with various stakeholders to deliver high-quality data engineering solutions.

  • Data Pipeline Engineering: Design and build scalable, high-performance ETL/ELT pipelines using Azure Data Factory and Databricks, handling ingestion and transformation of data from diverse internal and external sources.
  • Advanced Data Preparation & Transformation: Implement complex transformation logic using PySpark and SQL to standardize, cleanse, and normalize large-scale datasets including nested JSON.
  • Data Modeling: Create and maintain dimensional models (star/snowflake schemas) and structured outputs to support analytics, reporting, and regulatory use cases.
  • Performance Optimization: Profile and tune PySpark jobs for performance using techniques such as caching, partitioning, and broadcast joins. Ensure pipelines scale efficiently with increasing data volumes.
  • Governance & Quality Assurance: Apply robust data validation, quality checks, and maintain metadata lineage with Unity Catalog. Adhere to governance standards across the pipeline lifecycle.
  • Cross-Functional Collaboration: Partner with business analysts, product managers, data scientists, and QA teams to understand data requirements and deliver fit-for-purpose solutions.
Requirements
  • Bachelor s or Master s degree in Computer Science, Data Engineering, or equivalent practical experience.
  • Total experience of 6 to 8 years and 5+ years in data engineering roles with hands-on experience in PySpark, SQL, and Azure-based data ecosystems.
  • Strong background in building robust and maintainable pipelines using Azure Data Factory and Databricks.
  • Proven expertise in data modeling, schema design, and large-scale data preparation for analytics.
  • Proficient in Git, version control workflows, and CI/CD practices.
  • Solid understanding of data governance, metadata management, and data quality frameworks.
  • Exposure to Unity Catalog, Databricks Genie, or other AI-enhanced data engineering tools is preferred.

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