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Data Engineer

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Randstad

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Location:
India , Bengaluru

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

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Job Description:

As a Data Engineer, you will join Genus and work within the Data Platform Engineering team alongside the Data Platform Product Owner and Senior Data Engineer. In addition, you will be collaborating with the Data Operations Team and Data Enablement Team, along with Key stakeholders and other members of the team, such as Data Architects and Analysts, to design and deliver advanced data engineering solutions that enable scalable, secure, and high-performing data platforms.

Job Responsibility:

  • Design, develop, test, and deploy advanced data engineering solutions using Azure SQL Server, Python, PySpark, Databricks, and Azure Synapse
  • Optimize data models and queries for performance and resource efficiency
  • Build scalable data processing pipelines using Python and PySpark for large-scale data transformation and analytics
  • Implement and manage Databricks and Azure Synapse environments for big data processing and analytics
  • Develop and maintain data transformation models in dbt and Azure Data Factory
  • Ensure proper source control and deployment practices using Git and CI/CD tools (Azure DevOps, GitHub)
  • Collaborate with stakeholders to understand requirements and deliver technical solutions aligned with business needs
  • Guarantee data accuracy and integrity through data quality checks and cleansing processes
  • Performance tuning of SQL queries and data processing scripts
  • Manage and optimize the data platform for cost and performance, including proactive monitoring and self-healing design patterns

Requirements:

  • Bachelors Degree or Equivalent in Computing related subject
  • SQL / T-SQL and analytical data warehouse development – 8+ years
  • Apache Spark experience using Python, PySpark and SparkSQL at scale – 5+ years
  • Expertise on performance optimisation and production stability of the data workloads – 3+ years
  • Expertise on building metadata-driven, reusable data pipelines using Databricks and ADF – 3+ years
  • Hands-on experience working with Delta-based datasets, multi-layer Lakehouse architectures, and evolving schemas – 3+ years
  • Good knowledge of Unity Catalog, including governed data access, catalogs and schemas, and secure data sharing across teams – 2+ years
  • Design and operation of batch and incremental pipelines integrating Databricks with ADF, dbt, Airflow, and external source systems – 3+ years
  • Strong experience integrating Databricks with Azure services such as ADLS Gen2, Azure SQL / Synapse, and cloud-native security services – 3+ years
  • Experience implementing structured logging, pipeline metrics, and operational monitoring for data ingestion workloads, including failure handling and alerting – 3+ years
  • CI/CD-driven deployment of Databricks assets using Azure DevOps, GitHub, or similar tools – 3+ years
  • Experience working in Agile delivery environments (SAFe or similar)
  • Strong communication skills and ability to work across platform, analytics, and business teams
  • Comfortable operating in fast-paced environments with production responsibility

Nice to have:

  • Databricks Certified Professional
  • Dbt Certified
  • Microsoft Certified

Additional Information:

Job Posted:
February 28, 2026

Expiration:
April 13, 2026

Employment Type:
Fulltime
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