Data Engineer — Scalable Pipelines & Cloud Data Solutions

Lonvec Technologies Private Limited

Washington (IL)

On-site

USD 90,000 - 150,000

Full time

8 days ago

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Job summary

Deloitte is seeking an experienced Data Engineer to join its technology team and work on enterprise-level data solutions. The ideal candidate will design, develop, and maintain scalable data pipelines, data platforms, and analytics solutions.

You will build data ingestion and transformation processes using Python and Spark, work with cloud data platforms and data warehouses, optimize pipelines for performance and reliability, validate data quality, and collaborate with Data Scientists, Analysts,

Qualifications

  • Experience designing scalable data pipelines and data platforms.
  • Strong coding in Python and SQL for ETL/ELT.
  • Proficiency with Spark, Hadoop, and cloud data warehouses.

Responsibilities

  • Design, develop, and maintain scalable data pipelines and ETL workflows.
  • Build data ingestion and transformation processes.
  • Develop data processing solutions using Python and Spark.
  • Work with cloud data platforms and data warehouses.
  • Optimize pipelines for performance and reliability.
  • Ensure data quality and governance in collaboration with teams.

Skills

Python Programming
Advanced SQL
ETL / ELT Development
Apache Spark / PySpark
Hadoop
Snowflake
Databricks
Apache Kafka
Airflow
AWS Glue
Azure Data Factory
Cloud Data Platforms
Data Warehousing
Data Modeling

Tools

PySpark
Spark
Hadoop
Snowflake
Databricks
Kafka
Airflow
AWS Glue
Azure Data Factory

Job description

Deloitte is seeking an experienced Data Engineer to join its technology team and work on enterprise-level data solutions. The ideal candidate will design, develop, and maintain scalable data pipelines, data platforms, and analytics solutions.

You will build data ingestion and transformation processes using Python and Spark, work with cloud data platforms and data warehouses, optimize pipelines for performance and reliability, validate data quality, and collaborate with Data Scientists, Analysts,

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