Face To Face Interview (Senior Data Engineer)

Ikrux; Bengaluru; On-site; INR 3,000,000 - 4,200,000; Full time

Job summary

Ikrux in Bengaluru is seeking a Senior Data Engineer with 7–9 years of experience to design and build scalable data platforms on AWS.

You will work with PostgreSQL, AWS Glue, EMR, Spark, Redshift, and other AWS services, implementing ETL/ELT, data migrations, and CI/CD. Knowledge of data warehousing, dim modeling, and real-time/batch processing is required.

Experience with REST APIs, data quality, and AI/ML platforms is a plus; Bengaluru-based client work.

Qualifications

• 7–9 years of data engineering experience in enterprise environments.
• Strong expertise in PostgreSQL, AWS services, and data warehousing.
• Experience with ETL/ELT, data migration, data quality, and CI/CD.
• Familiarity with AI/ML platforms and cloud-native architectures is a plus.

Responsibilities

• Design and build scalable data platforms on AWS.
• Develop ETL/ELT processes and data migrations.
• Ensure data quality, validation, and CI/CD pipelines.
• Integrate REST APIs and enable real-time and batch data processing.

Skills

PostgreSQL

AWS RDS

SQL

Python

PySpark

AWS Glue

EMR

Redshift

Athena

Lambda

Kinesis

Kafka/MSK

Terraform

Data Warehousing

ETL/ELT

Data Quality

REST APIs

CI/CD

Jenkins

Git

AI/ML

Tools

AWS Glue

EMR

Spark

Redshift

Athena

Lambda

S3

Kinesis

Kafka/MSK

SageMaker

Terraform

Job description

Location: Bangalore Client Location

Experience: 7–9 years

Looking for an experienced Senior Data Engineer with expertise in PostgreSQL, Advanced SQL, Python, Data Warehousing, Dimensional Modeling, and AWS Cloud. Strong hands‑on experience in building scalable data platforms using AWS Glue, EMR, Spark, Redshift, Athena, Lambda, S3, Kinesis, Kafka/MSK, Event Bridge, SQS, SNS, SageMaker, and Terraform (IaC).

Must have experience in ETL/ELT development, data migration, data quality, data validation, REST API integrations, CI/CD, and real-time/batch data processing. Knowledge of AI/ML platforms, cloud-native data engineering, and modern data lake/warehouse architectures is a plus.

Key Skills: PostgreSQL, AWS RDS, SQL, Python, PySpark, AWS Glue, EMR, Redshift, Athena, Lambda, Kinesis, Kafka/MSK, Terraform, Data Warehousing, ETL/ELT, Data Quality, REST APIs, CI/CD, Jenkins, Git, AI/ML.