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Navixus | Tech Mahindra

Tech Lead

Posted An Hour Ago
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Hybrid
Bengaluru, Bengaluru Urban, Karnataka
Senior level
Hybrid
Bengaluru, Bengaluru Urban, Karnataka
Senior level
Lead design, development, and maintenance of robust, fault-tolerant data ingestion pipelines for the EY.ai Data Marketplace. Improve stability, optimization, and traceability of data assets; collaborate across ingestion, consumption, and activation phases; research and implement scalable data products using Azure and big data technologies.
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Job Summary
Job Role: Senior Data Engineer (Manager Level)
Location: Bhubaneswar / Hyderabad / Bangalore

Requirement:
We are looking for an experienced Senior Data Engineer (Manager Level) with 8+ years of experience for the EYDM Ingestion team. JD attached for reference.

Key Responsibilities:
  • Collaborate to identify and drive continuous improvements in the EY.ai Data Marketplace (EYDM) data assets and services.
  • Participate in design and development sessions to enhance data asset creation and ingestion pipelines, focusing on stability, optimization, and traceability.
  • Develop, test, and maintain robust data pipelines and processes.
  • Build resilient, fault tolerant, and modular code to ensure high availability of pipelines and services.
  • Research and implement innovative approaches to build world class data products and services.
  • Actively collaborate across teams to ensure smooth transitions across Ingestion, Consumption, and Activation phases.

Must Have Skills & Attributes:
  • Azure Data Factory (ADF): Expertise in developing and managing pipelines, triggers, activities, and data flows.
  • Azure Databricks: Strong experience with Databricks, including notebooks, jobs, clusters, and Apache Spark.
  • Programming: Proficiency in Python, PySpark, and SQL for data processing and transformation.
  • ETL & Data Integration: Hands on experience with ETL processes using ADF and Databricks across multiple data sources.
  • Cloud & Data Storage: Familiarity with Azure services such as Azure SQL Database, Blob Storage, and Data Lake Storage.
  • Big Data Processing: Experience with large scale data processing using Apache Spark.
  • Data Warehousing & Modelling: Strong understanding of data warehousing concepts and scalable data modelling techniques.

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