Senior Data Professional

1 week ago

Meerut, Uttar Pradesh, India beBeeDataEngineer Full time ₹ 15,00,000 - ₹ 20,00,000
About the Role

We're seeking a seasoned data professional to spearhead the design, development, and management of data pipelines and transformation frameworks that underpin analytics, reporting, and business intelligence capabilities across our enterprise.

This pivotal role will involve collaborating closely with cross-functional teams, including data architects, platform engineers, and DevOps experts, to build scalable, resilient, and efficient data engineering solutions using cutting-edge Azure tools and best practices.

Key Responsibilities:

  • Data Pipeline Design & Development: Design and build scalable ETL/ELT pipelines using Azure Data Factory (ADF), Azure Databricks (Spark), and Azure Synapse Analytics.
  • Large-Scale Data Transformations: Develop and optimize PySpark/Spark SQL jobs for batch and streaming data transformations.
  • Data Ingestion & Availability: Ingest data from various sources, including Apache Kafka, REST APIs, and RDBMS, ensuring real-time or near-real-time availability.
  • Data Modeling Strategies: Implement data modeling strategies (star schema, snowflake schema) for analytics consumption layers in Synapse or ADLS.
  • CICD Pipelines: Collaborate with DevOps teams to automate deployment using CI/CD pipelines (Azure DevOps, GitHub Actions, etc.).
  • Monitoring & Optimization: Monitor, troubleshoot, and optimize data workflows for performance, cost-efficiency, and reliability.
  • Coding Standards & Reviews: Follow coding standards, participate in peer reviews, and maintain version-controlled code in Git repositories.
  • Data Quality Checks: Support data quality checks, logging, alerting, and observability mechanisms for production workloads.
  • Sprint Ceremonies & Task Estimation: Participate in sprint ceremonies and contribute to task estimation and delivery planning.

Must-Have Skills:

  • Data Engineering Expertise: 5+ years of experience in data engineering roles.
  • Azure Data Services: Hands-on experience with:
    • Azure Data Factory (ADF) – building pipelines, triggers, linked services.
    • Azure Databricks – building and managing Spark jobs in PySpark.
    • Azure Synapse Analytics – data warehousing, SQL queries, workspace orchestration.
    • Apache Kafka – consuming and processing real-time data streams.
  • Programming Languages: Strong in SQL, Python, and Spark for data manipulation and transformation.
  • CI/CD Practices: Exposure to CI/CD practices (Azure DevOps, Git workflows, build/release pipelines).
  • Data Architecture: Understanding of data lake architecture and modern data warehousing principles.

Nice-to-Have Skills:

  • Specialized Tools: Experience with Delta Lake, Event Hub, or Azure Stream Analytics.
  • Infrastructure-as-Code: Familiarity with infrastructure-as-code tools like Terraform or ARM templates.
  • Data Governance: Exposure to Data Governance, Data Quality frameworks, or metadata management.
  • Security & Access Control: Understanding of networking, security, and access control in Azure data services

Preferred Certifications:

  • Azure Data Engineer Associate: Microsoft Certified: Azure Data Engineer Associate.
  • Databricks Associate Developer: Databricks Certified Associate Developer for Apache Spark.
  • Azure Fundamentals: Azure Fundamentals (AZ-900) – optional but helpful

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