Data Engineer

Techcarrot Fz-llc

Dadri

On-site

INR 1,800,000 - 3,200,000

Full time

14 days+
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Job summary

Techcarrot Fz-llc is seeking a Data Engineer to design and deploy end-to-end data pipelines on the Azure Data Platform. You will own projects, build scalable ingestion frameworks, and transform data using Python/PySpark across diverse data sources.

The role emphasizes batch and near-real-time processing, optimized Spark workloads, data quality checks, and CI/CD with Azure DevOps. Collaboration with architects and BI teams is essential.

Qualifications

  • 46 years of overall experience in Data Engineering / Data Platform development.
  • Preferably 4+ years of hands-on experience with Microsoft Azure Data Platform technologies.
  • Strong hands-on experience with Azure Data Factory, Databricks, SQL and Python/PySpark.
  • Bachelor's degree in Computer Science, Information Technology, Engineering or a related discipline.
  • Experience delivering at least one or more end-to-end Azure data engineering projects.
  • Good understanding of data warehousing, data lake and modern data platform concepts.
  • Strong analytical and problem-solving skills.
  • Ability to work independently and manage multiple technical activities.
  • Good written and verbal communication skills.

Responsibilities

  • Independently understand business and technical requirements and translate them into scalable data engineering solutions.
  • Take end-to-end ownership of assigned projects, modules and data pipelines with minimal supervision.
  • Design, develop, test and deploy robust end-to-end data pipelines on the Azure Data Platform.
  • Build scalable and reusable data ingestion and transformation frameworks using Azure Data Factory and Azure Databricks.
  • Develop data transformation and processing logic using Python, PySpark and SQL.
  • Work with structured, semi-structured and unstructured data from databases, APIs, files and other enterprise data sources.
  • Design and implement batch and, where required, near-real-time data processing solutions.
  • Develop optimized Databricks workloads using Apache Spark and Delta Lake.
  • Perform data analysis, profiling and validation to identify data quality, completeness and consistency issues.
  • Implement appropriate data quality checks, error handling, logging and monitoring within data pipelines.
  • Troubleshoot data pipeline failures, performance issues and data discrepancies independently.
  • Optimize SQL queries, Spark jobs and data pipelines for performance and scalability.
  • Create reusable components and frameworks to improve development efficiency across projects.
  • Participate in solution design and technical discussions and provide recommendations on implementation approaches.
  • Implement CI/CD processes for data engineering components using Azure DevOps.
  • Deploy and manage ADF, Databricks and related Azure data components across development, test and production environments.
  • Prepare appropriate technical design, data mapping and operational documentation.
  • Collaborate with solution architects, analysts, BI developers, source-system teams and other engineering teams.
  • Support production deployments and troubleshoot post-production issues when required.

Skills

Azure Data Factory
Azure Databricks
ADLS Gen2
Azure Synapse
SQL
Python
PySpark
Databricks
Spark
CI/CD

Education

Bachelor's degree in CS/IT/Engineering

Tools

Azure DevOps
Git
Delta Lake

Job description

Responsibilities
  • Independently understand business and technical requirements and translate them into scalable data engineering solutions.
  • Take end-to-end ownership of assigned projects, modules and data pipelines with minimal supervision.
  • Design, develop, test and deploy robust end-to-end data pipelines on the Azure Data Platform.
  • Build scalable and reusable data ingestion and transformation frameworks using Azure Data Factory and Azure Databricks.
  • Develop data transformation and processing logic using Python, PySpark and SQL.
  • Work with structured, semi-structured and unstructured data from databases, APIs, files and other enterprise data sources.
  • Design and implement batch and, where required, near-real-time data processing solutions.
  • Develop optimized Databricks workloads using Apache Spark and Delta Lake.
  • Perform data analysis, profiling and validation to identify data quality, completeness and consistency issues.
  • Implement appropriate data quality checks, error handling, logging and monitoring within data pipelines.
  • Troubleshoot data pipeline failures, performance issues and data discrepancies independently.
  • Optimize SQL queries, Spark jobs and data pipelines for performance and scalability.
  • Create reusable components and frameworks to improve development efficiency across projects.
  • Participate in solution design and technical discussions and provide recommendations on implementation approaches.
  • Implement CI/CD processes for data engineering components using Azure DevOps.
  • Deploy and manage ADF, Databricks and related Azure data components across development, test and production environments.
  • Prepare appropriate technical design, data mapping and operational documentation.
  • Collaborate with solution architects, analysts, BI developers, source-system teams and other engineering teams.
  • Support production deployments and troubleshoot post-production issues when required.
Requirements
  • Strong hands-on experience with:
    • Azure Data Platform
      • Azure Data Factory (ADF) pipelines, datasets, linked services, triggers, parameterization and reusable frameworks
      • Azure Databricks
      • Azure Data Lake Storage Gen2 (ADLS Gen2)
      • Azure Synapse Analytics / Azure SQL
      • Azure Key Vault
      • Azure Monitor / Log Analytics or equivalent monitoring capabilities
      • Azure Event Hubs exposure/experience is preferred
    • Databricks & Data Processing
      • Strong hands-on experience with Databricks and Apache Spark
      • Strong PySpark development skills
      • Experience with Delta Lake / Delta tables
      • Understanding of Medallion or similar layered data architectures
      • Experience implementing incremental and full-load processing patterns
      • Ability to troubleshoot and optimize Spark workloads
      • Experience with Databricks Workflows/Jobs
      • Knowledge of Unity Catalog is preferred
    • SQL & Python
      • Strong SQL development skills
      • Ability to write and optimize complex SQL queries
      • Experience with joins, CTEs, window functions and analytical queries
      • Strong working knowledge of Python
      • Ability to develop reusable Python/PySpark modules and utilities
    • DevOps / CI-CD
      • Hands-on experience with Azure DevOps
      • Git-based source control
      • Branching and code-management practices
      • CI/CD implementation for Azure Data Factory and Databricks
      • Experience deploying solutions across multiple environments
    Qualifications & Experience
    • 46 years of overall experience in Data Engineering / Data Platform development.
    • Preferably 4+ years of hands-on experience with Microsoft Azure Data Platform technologies.
    • Strong hands-on experience with Azure Data Factory, Databricks, SQL and Python/PySpark.
    • Bachelors degree in Computer Science, Information Technology, Engineering or a related discipline.
    • Experience delivering at least one or more end-to-end Azure data engineering projects.
    • Good understanding of data warehousing, data lake and modern data platform concepts.
    • Strong analytical and problem-solving skills.
    • Ability to work independently and manage multiple technical activities.
    • Good written and verbal communication skills.
    Preferred Skills
    • Microsoft Azure / Databricks certifications.
    • Experience with Unity Catalog and Databricks governance.
    • Experience with REST API-based data ingestion.
    • Knowledge of dimensional modelling and data warehouse concepts.
    • Experience working with Power BI or downstream analytics platforms.
    • Exposure to streaming/event-driven data processing.
    • Experience working in enterprise-scale Azure environments.
    Job Details
    • Job Type: Full time
    • Job Opening Name: Data Engineer
    • State: Telangana
    • Country: India
    • Location: Hyderabad, Noida/ Chennai
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