Senior Data Architect

2 weeks ago

Jaipur, Rajasthan, India beBeeDataEngineer Full time ₹ 1,50,00,000 - ₹ 2,50,00,000

Job Title:

Data Engineer

Location:

Mumbai, 5th Floor, 3, North Avenue, Maker Maxity, Bandra Kurla Complex

Duration:

12+ months, likely long term

Work Mode:

Hybrid

Notice Period:

Immediate - 15days

About the Role:

We are looking for a skilled Data Engineer to join our team. The successful candidate will be responsible for designing, developing, and maintaining batch and streaming data pipelines.

  • Required Skills:
  • Experience in PySpark: Strong Experience in PySpark
  • Hands-on expertise in building scalable data pipelines using PySpark: Hands-on expertise in building scalable data pipelines using PySpark.
  • Proficiency in using Spark SQL, DataFrame, and RDD APIs: Proficiency in using Spark SQL, DataFrame, and RDD APIs to implement complex business logic.
  • Programming Skills: Proficient Programming Skills
  • Coding Skills: Solid coding skills in Python (preferred), with strong fundamentals in data structures, algorithms, and software engineering principles.
  • Data Pipeline Development: Data Pipeline Development
  • ETL/ELT Process Understanding: Understanding of ETL/ELT processes and best practices for data transformation, data quality, and performance optimization.
  • Modern Data Engineering Ecosystem Knowledge: Knowledge of Modern Data Engineering Ecosystem
  • Distributed Data Processing Knowledge: Familiarity with the current data engineering landscape including distributed data processing, storage systems, and workflow orchestration tools.
  • Cloud Data Platform Experience: Cloud Data Platform Experience (Preferably AWS)
  • Cloud Services Experience: Experience working with cloud services such as:
    • AWS S3 (data lake)
    • AWS Glue / EMR (for Spark workloads)
    • AWS Lambda, Step Functions, or similar for orchestration/integration
    • Redshift or other cloud data warehouses
  • Spark API Expertise: Spark API Expertise for Business Logic Implementation
  • Business Logic Implementation Ability: Ability to choose and apply the right Spark APIs (DataFrame, Dataset, RDD) for performance-efficient implementation of business logic at scale.

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