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Open nowPosted 5 days ago

Data Engineer / Data Scientist

Intervoice1,513 open roles

Where
IND Bangalore - MTP C4, 3rd Flr
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Your applicationOpen nowData Engineer / Data ScientistIntervoice · IND Bangalore - MTP C4, 3rd Flr

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The clock on this job

Early applications get read.

8.0% of postings close within 7 days. Measured by our own scanner across the market. Intervoice postings stay open a median of 22 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 8.0%7 days
  4. 15.0%14 days
  5. 34.2%30 days
This job: posted 5 days ago

Intervoice median: 22 days open

The posting

Job Title:

Data Engineer / Data Scientist

Job Description

We're Concentrix. The intelligent transformation partner. Solution-focused. Tech-powered. Intelligence-fueled.

The global technology and services leader that powers the world’s best brands, today and into the future. We’re solution-focused, tech-powered, intelligence-fueled. With unique data and insights, deep industry expertise, and advanced technology solutions, we’re the intelligent transformation partner that powers a world that works, helping companies become refreshingly simple to work, interact, and transact with. We shape new game-changing careers in over 70 countries, attracting the best talent.

The Concentrix Technical Products and Services team is the driving force behind Concentrix’s transformation, data, and technology services. We integrate world-class digital engineering, creativity, and a deep understanding of human behavior to find and unlock value through tech-powered and intelligence-fueled experiences. We combine human-centered design, powerful data, and strong tech to accelerate transformation at scale. You will be surrounded by the best in the world providing market leading technology and insights to modernize and simplify the customer experience. Within our professional services team, you will deliver strategic consulting, design, advisory services, market research, and contact center analytics that deliver insights to improve outcomes and value for our clients. Hence achieving our vision.

Our game-changers around the world have devoted their careers to ensuring every relationship is exceptional. And we’re proud to be recognized with awards such as "World's Best Workplaces," “Best Companies for Career Growth,” and “Best Company Culture,” year after year.

Join us and be part of this journey towards greater opportunities and brighter futures.

Job Description: Data Engineer / Data Scientist

Experience: 5–8 years Position Type: Immediate Requirement Location: Remote

Role Summary

We are looking for an experienced Data Engineer / Data Scientist with strong hands-on expertise in Python, PySpark, Azure Databricks, and MLOps. The candidate should be capable of working independently as an individual contributor while collaborating effectively with cross-functional teams.

The ideal candidate will have experience developing scalable batch and streaming data pipelines, working on machine learning projects, debugging Spark applications, and supporting model deployment.

Key Responsibilities

  • Develop scalable data processing solutions using Python, PySpark, and Azure Databricks.
  • Build and maintain batch and streaming data pipelines.
  • Develop and optimize Spark DataFrame-based transformations.
  • Debug and troubleshoot Spark jobs in Azure Databricks.
  • Implement Delta Lake solutions for data reliability, versioning, and efficient querying.
  • Develop APIs using Python or Scala for data and machine learning applications.
  • Support machine learning projects, MLOps workflows, and model deployment activities.
  • Work with Azure services for data ingestion, storage, security, integration, and processing.
  • Configure and manage Databricks job clusters and notebook workflows.
  • Validate processed data by building and executing DataFrame-based checks.
  • Collaborate with technical and business teams while independently owning assigned deliverables.

Must-Have Skills

  • Strong hands-on expertise in Python and PySpark.
  • Good knowledge of Microsoft Azure and Azure Databricks.
  • Hands-on experience with MLOps practices and tools.
  • Basic understanding of machine learning model deployment.
  • Practical experience working on machine learning projects.
  • Experience developing and debugging Spark-based applications.
  • Ability to work independently and interact effectively with project teams.

Additional Relevant Skills

  • Hands-on experience in Databricks notebook development.
  • Strong experience with Spark DataFrames using PySpark or Scala.
  • Experience debugging and optimizing Spark jobs in Azure Databricks.
  • Knowledge of API development using Python or Scala.
  • Working knowledge of Azure services, including:Azure Event Hubs Azure Storage Accounts Azure Key Vault Azure Service Bus Azure Functions Azure Data Lake Storage
  • Understanding of Databricks job clusters and compute configurations.
  • Hands-on experience implementing Azure cloud-based data solutions.
  • Knowledge of real-time streaming technologies such as Kafka.
  • Experience developing batch and streaming pipelines using Event Hubs, Kafka, or IoT data sources.
  • Experience implementing Delta Lake solutions for data reliability, versioning, and query performance.
  • Working knowledge of GitHub or similar version-control platforms.

Preferred Technical Exposure

  • MLflow or similar tools for experiment tracking and model lifecycle management.
  • CI/CD implementation for data and machine learning workloads.
  • Performance tuning of Spark applications and Databricks workloads.
  • Data quality validation, monitoring, and production support.
  • Secure integration of Azure services using managed identities and secrets.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Information Technology, or a related discipline.
  • 5–8 years of relevant experience in data engineering, data science, machine learning, or cloud analytics.

Location:

IND Bangalore - MTP C4, 3rd Flr

Language Requirements:

Time Type:

Full time

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