Data Engineer

Lonvec Technologies Private Limited; Washington (IL); On-site; USD 90,000 - 150,000; Full time

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 be responsible for designing, developing, and maintaining scalable data pipelines, data platforms, and analytics solutions.The candidate will work with modern data technologies, cloud platforms, and big data frameworks to transform complex datasets into meaningful business insights.Design and develop 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 data pipelines for performance and reliability.Perform data validation and ensure data quality.Collaborate with Data Scientists, Analysts, and Business Teams.Troubleshoot data issues and implement solutions.Follow data governance and security best practices.

Requirements

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