Data Engineer

Bct Consulting; Bengaluru; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Bct Consulting in Bengaluru seeks Data Engineer with 3 to 5 years' hands-on experience in Spark, SQL, Python and AWS to build scalable data pipelines. Immediate joiners preferred and this role focuses on cloud-native data platforms and data quality across diverse sources.

You will design and implement ETL/ELT processes, optimize performance and collaborate with teams to deliver reliable data solutions for complex data workloads.

Qualifications

• Hands-on experience designing scalable ETL/ELT pipelines using Spark and Python.
• Strong SQL skills with performance optimization for large datasets.
• Experience building cloud-native data platforms on AWS.

Responsibilities

• Design and develop scalable ETL/ELT pipelines using Spark and Python.
• Build and optimize large-scale data processing solutions.
• Develop cloud-native data platforms on AWS.
• Create efficient SQL queries and optimize data performance.
• Work with structured and unstructured data across multiple sources.
• Collaborate with cross-functional teams to deliver reliable data solutions.
• Ensure data quality, monitoring, and pipeline reliability.
• Contribute to building modern, scalable data architectures.

Skills

Apache Spark

Advanced SQL

Python

AWS

ETL/Data Pipeline

Data Warehousing

Performance Optimization

Job description

We're hiring for Data Engineer professionals with strong expertise in Spark, SQL, Python, and AWS.

Experience: 3 to 5 years

Immediate Joiners Preferred

Location: Bengaluru

Skills Required:

• Apache Spark (PySpark/Spark SQL)
• Advanced SQL
• Python
• AWS (S3, Glue, EMR, Redshift, Athena, Lambda)
• ETL/Data Pipeline Development
• Data Warehousing Concepts
• Performance Optimization & Data Processing

Experience:

3 -5 Years in Data Engineering with hands-on experience in building scalable data pipelines and cloud-based data solutions.

What You'll Work On:

• Design and develop scalable ETL/ELT pipelines using Spark and Python.
• Build and optimize large-scale data processing solutions.
• Develop cloud-native data platforms on AWS.
• Create efficient SQL queries and optimize data performance.
• Work with structured and unstructured data across multiple sources.
• Collaborate with cross-functional teams to deliver reliable data solutions.
• Ensure data quality, monitoring, and pipeline reliability.
• Contribute to building modern, scalable data architectures.