Data Engineer / Data Scientist
New
J
JobgetherData engineering
Based in IndiaFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 5–8 years of relevant professional experience in data engineering, data science, machine learning, or cloud analytics.
- Required Skills
- PythonMachine LearningMicrosoft AzureApache KafkaSparkMLOpsPySpark
Requirements
- Hold a Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Information Technology, or a related discipline.
- Have 5–8 years of relevant professional experience in data engineering, data science, machine learning, or cloud analytics.
- Bring strong hands-on expertise in Python and PySpark.
- Have good knowledge of Microsoft Azure and Azure Databricks.
- Have hands-on experience with MLOps practices and tools.
- Have practical experience supporting machine learning projects and a basic understanding of model deployment.
- Have strong experience developing and debugging Spark-based applications.
- Have experience with Databricks notebook development and Spark DataFrames using PySpark or Scala.
- Have experience optimizing Spark jobs and Databricks workloads.
- Have experience developing APIs using Python or Scala.
- Have working knowledge of Azure Event Hubs, Storage Accounts, Key Vault, Service Bus, Azure Functions, and Azure Data Lake Storage.
- Have working knowledge of GitHub or similar version-control platforms.
Responsibilities
- Develop scalable data processing solutions using Python, PySpark, and Azure Databricks.
- Build, maintain, and optimize batch and real-time streaming data pipelines.
- Develop Spark DataFrame-based transformations and data processing workflows.
- Debug, troubleshoot, and optimize Spark applications and Databricks jobs.
- Implement Delta Lake solutions to improve data reliability, versioning, and query performance.
- Develop APIs using Python or Scala for data and machine learning applications.
- Support machine learning initiatives, MLOps workflows, and model deployment activities.
- Work with Azure services for data ingestion, storage, security, integration, and processing.
- Build and execute DataFrame-based data validation and quality checks.
- Collaborate with technical and business stakeholders while independently managing assigned deliverables.
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