Data Engineering and Analytics Expert

5 days ago


Noida, Uttar Pradesh, India Digihelic Solutions Private Limited Full time

About the Role:

We are seeking a seasoned Data Engineer and Analyst to join our team at Digihelic Solutions Private Limited. This role requires a strong blend of data engineering and analytics skills, with a focus on building and maintaining robust data pipelines and delivering actionable insights.

The ideal candidate will have extensive experience with cloud platforms (AWS/Azure), ETL processes, SQL, Databricks, PySpark/Apache Spark, and either NiFi or Hive.

Responsibilities:

  • Data Pipeline Development & Management: Design, develop, and maintain scalable and efficient ETL/ELT pipelines using tools like Databricks, PySpark/Apache Spark, and either NiFi or Hive.
  • Ingest, transform, and load data from diverse sources into cloud-based data warehouses and data lakes.
  • Orient data pipelines for performance, reliability, and cost-effectiveness.
  • Cloud Platform Expertise (AWS/Azure): Design and implement data solutions on either AWS or Azure cloud platforms.
  • Utilize cloud-native services for data storage, processing, and analytics.
  • Manage and optimize cloud resources for data engineering workloads.
  • Data Warehousing & Data Lake Management: Design and implement data warehousing and data lake solutions for analytical purposes.
  • Develop and maintain data models and schemas.
  • Ensure data quality, consistency, and integrity.
  • Programming & Scripting: Develop and maintain data processing scripts using Python and/or Scala.
  • Utilize PySpark/Apache Spark for large-scale data processing and analysis.
  • Implement data transformations and business logic using SQL.
  • Data Analysis & Reporting: Analyze data to identify trends, patterns, and insights.
  • Develop and maintain data visualizations and dashboards.
  • Generate reports and presentations for stakeholders.
  • Tool Proficiency (NiFi or Hive): Utilize either Apache NiFi for data flow automation and management or Apache Hive for data warehousing and SQL querying.
  • Design and implement data flows or Hive queries for data processing and analysis.
  • Collaboration & Communication: Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
  • Communicate effectively with technical and non-technical audiences.
  • Participate in agile development methodologies.
  • Troubleshooting & Performance Optimization: Identify and resolve data pipeline and system issues.
  • Orient data processing and query performance.
  • Implement monitoring and alerting systems.


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