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Open nowFirst seen 6 days ago

Azure Big Data Engineer | 4 to 8 Yrs | WFO | SOW 2024 2579

PradeepIT Consulting Services Pvt Ltd2,005 open roles

Where
Bangalore, Karnataka, India
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Your applicationOpen nowAzure Big Data Engineer | 4 to 8 Yrs | WFO | SOW 2024 2579PradeepIT Consulting Services Pvt Ltd · Bangalore, Karnataka, India

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Share of postings closed within
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  3. 12.3%7 days
  4. 19.7%14 days
  5. 35.6%30 days
  6. 58.0%60 days
This job: first seen 6 days ago

The posting

Job Title: Azure Big Data Engineer

Years of Experience: 4 to 8 Years

Relevant Experience: 5 Years

Headcount: 02

Job/Work type: WFO (5 days a week for First 3 months, later its Hybrid 3 days a week)

Location: Bangalore (preferred), Hyderabad

Time Zone: IST time zone (In IST 10:00 am to 7:00 pm)

Project Name: -

Client: Bosch

End Client: -

Other details:

Interview details:

  • L1 round - Face 2 Face, Bosch locations at Bangalore or Hyderabad (with Bosch team)
  • L2 round - Virtual with end client.

Mandatory Skills:

Azure Skills Like

  • Azure Databricks
  • Azure Synapse
  • Azure Functions
  • Azure Data Lake
  • Azure Integration Services
  • Azure API Management
  • CI/CD and PowerShell Scripts
  • ADF
  • ETL Pipelines
  • Unity Catalog
  • Azure SQL Database
  • SQL Coding
  • Storage Account, Azure Data Explorer, Spark Structured Streaming, ADF, Netezza SQL queries, Data lineage, Spark jobs.

Role & Responsibilities / Job Description:

  • Overall 4 to 8 years of experience with a minimum 4+ years of relevant professional work experience.
  • Design, implement, and maintain data pipelines for data ingestion, processing, and transformation in Azure.
  • Work together with data analysts to understand the needs for data and create effective data workflows.
  • Create and maintain data storage solutions including Azure Databricks, Azure Functions, Azure Data Lake, Azure Synapse, Azure Integration Services, Azure API Management, CI/CD and PowerShell Scripts. ADF, ETL Pipelines, Unity Catalog, Azure SQL Database, SQL Coding, Azure SQL Database, Azure Data Lake.
  • Utilizing Azure Data Factory to create and maintain ETL (Extract, Transform, Load) operations using ADF pipelines.
  • Hands-On Experience working on Data Bricks for implementing Transformations and Delta Lake.
  • Hands-On Experience working on Serverless SQL Pool, Dedicated SQL Pool.
  • Use ADF pipelines to orchestrate the end to end data transformation including the execution of DataBricks notebooks.
  • Should have experience working on Medallion Architecture.
  • Experience working on CI/CD pipelines using Azure DevOps.
  • Attaching both ADF and ADB to DevOps.
  • Creating and managing Azure infrastructure across the landscape using Bicep.
  • Implementing data validation and cleansing procedures will ensure the quality, integrity, and dependability of the data.
  • Improve the scalability, efficiency, and cost-effectiveness of data pipelines.
  • Monitoring and resolving data pipeline problems will guarantee consistency and availability of the data.
  • Good to have exposure on Power BI, Power Automate.

Task description:

  • We are looking for a Data Engineer to join our growing team of analytics experts.
  • The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams.
  • The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
  • Should have good hands on implementing Incremental/Delta loads.
  • Develop and Support activities of development in Projects and Automation solutions for customers

Deliverables Expected

The following shall be the deliverables as per project documented quality process:

  1. Updated requirements document / Detailed Bug Analysis report
  2. Concept document (wherever applicable)
  3. Design document (for all features)
  4. Test specification document
  5. Source code
  6. Review report
  7. Test report
  8. Filled review checklists
  9. Traceability matrix
  10. User manuals and related artifacts
  11. Filled pre-delivery checklist (PDC)
  12. Release Note & release mails
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