drjobs TechOps-DE-CloudOps AMS-Azure DataOps Engineer-Senior

TechOps-DE-CloudOps AMS-Azure DataOps Engineer-Senior

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1 Vacancy
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Job Location drjobs

Delhi - India

Monthly Salary drjobs

Not Disclosed

drjobs

Salary Not Disclosed

Vacancy

1 Vacancy

Job Description

At EY youll have the chance to build a career as unique as you are with the global scale support inclusive culture and technology to become the best version of you. And were counting on your unique voice and perspective to help EY become even better too. Join us and build an exceptional experience for yourself and a better working world for all.

The opportunity

We are seeking a highly skilled and motivated Senior DataOps Engineer with strong expertise in the Azure data ecosystem. You will play a crucial role in managing and optimizing data workflows across Azure platforms such as Azure Data Factory Data Lake Databricks and Synapse. Your primary focus will be on building maintaining and monitoring data pipelines ensuring high data quality and supporting critical data operations. Youll also support visualization automation and CI/CD processes to streamline data delivery and reporting.

Your key responsibilities

  • Data Pipeline Management: Build monitor and optimize data pipelines using Azure Data Factory (ADF) Databricks and Azure Synapse for efficient data ingestion transformation and storage.
  • ETL Operations: Design and maintain robust ETL processes for batch and real-time data processing across cloud and on-premise sources.
  • Data Lake Management: Organize and manage structured and unstructured data in Azure Data Lake ensuring performance and security best practices.
  • Data Quality & Validation: Perform data profiling validation and transformation using SQL PySpark and Python to ensure data integrity.
  • Monitoring & Troubleshooting: Use logging and monitoring tools to troubleshoot failures in pipelines and address data latency or quality issues.
  • Reporting & Visualization: Work with Power BI or Tableau teams to support dashboard development ensuring the availability of clean and reliable data.
  • DevOps & CI/CD: Support data deployment pipelines using Azure DevOps Git and CI/CD practices for version control and automation.
  • Tool Integration: Collaborate with cross-functional teams to integrate Informatica CDI or similar ETL tools with Azure components for seamless data flow.
  • Collaboration & Documentation: Partner with data analysts engineers and business stakeholders while maintaining SOPs and technical documentation for operational efficiency.

Skills and attributes for success

  • Strong hands-on experience in Azure Data Factory Azure Data Lake Azure Synapse and Databricks
  • Solid understanding of ETL/ELT design and implementation principles
  • Strong SQL and PySpark skills for data transformation and validation
  • Exposure to Python for automation and scripting
  • Familiarity with DevOps concepts CI/CD workflows and source control systems (Azure DevOps preferred)
  • Experience in working with Power BI or Tableau for data visualization and reporting support
  • Strong problem-solving skills attention to detail and commitment to data quality
  • Excellent communication and documentation skills to interface with technical and business teamsStrong knowledge of asset management business operations especially in data domains like securities holdings benchmarks and pricing.

To qualify for the role you must have

  • 46 years of experience in DataOps or Data Engineering roles
  • Proven expertise in managing and troubleshooting data workflows within the Azure ecosystem
  • Experience working with Informatica CDI or similar data integration tools
  • Scripting and automation experience in Python/PySpark
  • Ability to support data pipelines in a rotational on-call or production support environment
  • Comfortable working in a remote/hybrid and cross-functional team setup

Technologies and Tools

Must haves

  • Azure Databricks: Experience in data transformation and processing using notebooks and Spark.
  • Azure Data Lake: Experience working with hierarchical data storage in Data Lake.
  • Azure Synapse: Familiarity with distributed data querying and data warehousing.
  • Azure Data factory: Hands-on experience in orchestrating and monitoring data pipelines.
  • ETL Process Understanding: Knowledge of data extraction transformation and loading workflows including data cleansing mapping and integration techniques.

Good to have

  • Power BI or Tableau for reporting support
  • Monitoring/logging using Azure Monitor or Log Analytics
  • Azure DevOps and Git for CI/CD and version control
  • Python and/or PySpark for scripting and data handling
  • Informatica Cloud Data Integration (CDI) or similar ETL tools
  • Shell scripting or command-line data
  • SQL (across distributed and relational databases)

What we look for

What we offer

EY Global Delivery Services (GDS) is a dynamic and truly global delivery network. We work across six locations Argentina China India the Philippines Poland and the UK and with teams from all EY service lines geographies and sectors playing a vital role in the delivery of the EY growth strategy. From accountants to coders to advisory consultants we offer a wide variety of fulfilling career opportunities that span all business disciplines. In GDS you will collaborate with EY teams on exciting projects and work with well-known brands from across the globe. Well introduce you to an ever-expanding ecosystem of people learning skills and insights that will stay with you throughout your career.

EY Building a better working world



EY exists to build a better working world helping to create long-term value for clients people and society and build trust in the capital markets.



Enabled by data and technology diverse EY teams in over 150 countries provide trust through assurance and help clients grow transform and operate.



Working across assurance consulting law strategy tax and transactions EY teams ask better questions to find new answers for the complex issues facing our world today.

Employment Type

Full Time

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