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Data Engineer- Azure Databricks- Senior Associate

PwC
Bengaluru, IND
Full-time
Senior · 4+ years experience
Onsite
Discovered 2 weeks ago
airflowazureazure-data-factoryazure-functionsdatabricksgit

Full Job Posting

Must Have:

  • 4+ years of experience working in Azure ADLS, Data Bricks, Data Flows, HDInsight, Azure Analysis services
  • Should be aware of Data Management concepts and Data Modelling
  • Good knowledge of Big Data frameworks and related technologies
  • Experience in Hadoop and Spark is mandatory
  • Should have expertise in extracting data from different source systems like flat files, XML sources, JSON, Parquet files, Big data appliances, RDBMS, etc.
  • Should have clear understanding of DW lifecycle and contributed in preparing
  • Detail Level Design document
  • Unit Test plans
  • Code review reports
  • Must have strong sql, understand joins, groups, functions & Stored procedures
  • Must have experience in Unit and Integration Test creation and verification
  • Proficient in creating documentation related to Project Architecture, Project end User Manual and - Operations Hand off guide
  • Should have good understanding of Data Migration processes, methods and project lifecycle
  • Good in Unix Shell Scripting skills
  • Strong analytical skills and troubleshooting skills
  • Should be well versed with quality processes and implementation
  • Excellent communication skills
  • Strong understanding of Cloud data migration processes, methods and project lifecycle
  • Good knowledge of Application DevOps tools (Git, CI/CD Frameworks)
  • Experience in Jenkins or Gitlab with rich experience in source code management like Code - Pipeline, Code Build and Code Commit
  • Desired Knowledge / Skills:
  • Certifications in Azure / Databricks
  • Experience in building stream-processing systems, using solutions such as Storm or Spark
  • Streaming
  • Experience in Big Data ML toolkits, such as Mahout, SparkML, or H2O
  • Experience in Azure functions
  • Knowledge in Python What Sets You Apart Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics Demonstrating Azure Databricks delivery across data modernization engagements Applying Databricks, Azure Data Factory, and Airflow in pipeline builds Translating complex data requirements into scalable engineering solutions Analyzing data architecture, modeling, and optimization opportunities Mentoring junior team members while managing assigned workstreams
  • Travel Requirements
  • Not Specified
  • Job Posting End Date

Responsibilities

  • Building Azure Databricks data pipelines and scalable data engineering solutions across cloud environments
  • Designing and maintaining data integration, transformation, and validation workflows for modern analytics platforms
  • Optimizing data models, query performance, and warehouse structures to support faster reporting and analysis
  • Applying Apache Airflow, Azure Data Factory, and Databricks tools to orchestrate dependable batch and streaming processes
  • Collaborating with client stakeholders to translate business needs into technical data architecture and delivery plans
  • Supporting data modernization efforts that migrate legacy platforms to cloud-native architectures
  • Reviewing code, pipeline logic, and data quality controls to validate consistency and support issue resolution
  • Mentoring junior team members on engineering methods, platform usage, and delivery practices
  • What You Must Have
  • At least a Bachelor's degree
  • At least 4 years of experience
  • Oral and written proficiency in English required
  • 4+ years of experience working in Azure ADLS, Data Bricks, Data Flows, HDInsight, Azure Analysis services
  • Should be aware of Data Management concepts and Data Modelling
  • Good knowledge of Big Data frameworks and related technologies
  • Experience in Hadoop and Spark is mandatory
  • Should have expertise in extracting data from different source systems like flat files, XML sources, JSON, Parquet files, Big data appliances, RDBMS, etc.
  • Should have clear understanding of DW lifecycle and contributed in preparing
  • Detail Level Design document
  • Unit Test plans
  • Code review reports
  • Must have strong sql, understand joins, groups, functions & Stored procedures
  • Must have experience in Unit and Integration Test creation and verification
  • Proficient in creating documentation related to Project Architecture, Project end User Manual and - Operations Hand off guide
  • Should have good understanding of Data Migration processes, methods and project lifecycle
  • Good in Unix Shell Scripting skills
  • Strong analytical skills and troubleshooting skills
  • Should be well versed with quality processes and implementation
  • Excellent communication skills
  • Strong understanding of Cloud data migration processes, methods and project lifecycle
  • Good knowledge of Application DevOps tools (Git, CI/CD Frameworks)
  • Experience in Jenkins or Gitlab with rich experience in source code management like Code - Pipeline, Code Build and Code Commit
  • Desired Knowledge / Skills:
  • Certifications in Azure / Databricks
  • Experience in building stream-processing systems, using solutions such as Storm or Spark
  • Streaming
  • Experience in Big Data ML toolkits, such as Mahout, SparkML, or H2O
  • Experience in Azure functions
  • Knowledge in Python
  • What Sets You Apart
  • Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics
  • Demonstrating Azure Databricks delivery across data modernization engagements
  • Applying Databricks, Azure Data Factory, and Airflow in pipeline builds
  • Translating complex data requirements into scalable engineering solutions
  • Analyzing data architecture, modeling, and optimization opportunities
  • Mentoring junior team members while managing assigned workstreams

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