Data Engineer (Mid)Hyderabad6+yrs

Arminus

Job Location:

Hyderabad - India

Monthly Salary: Not Disclosed

Posted on: 8 days ago

Vacancies: 1 Vacancy

Job Summary

Data Engineer (Mid) - 4777

IT Development Team

Overview

Location: onsite Hyderabad

Employment Type: full time

Experience: 6 years

Compensation: INR-

Interview Process:

L1: Technical interview with Engineer (Virtual)

L2: SME interview (Virtual)

L3: Final round with Manager (Onsite)

Job Title

Data Engineer (Mid)

Experience Required

Extracted: 6 years of hands-on experience building enterprise-scale applications data platforms or

distributed systems.

Strong experience in Python (5 years)

Big Data (6 years)

Hands-on expertise with AWS services particularly:

EMR (mandatory and most critical skill)

EC2

Lambda

Candidate should have experience with EMR performance and cost optimization

Overview

Seeking a Data Engineer / Backend Developer to design build and operate cloud-native API-driven Big Data

systems. The role focuses on AWS EMR and Spark-based batch processing with strong emphasis on Python

development workflow orchestration (Airflow) and production reliability.

Key Responsibilities

Design and develop API-driven systems to govern manage and monitor large-scale batch Big Data

applications.

Build scalable backend services and data engineering solutions supporting data processing and operational

workflows.

Develop and maintain data transformation processes using Spark SQL Hive Python Scala and related

technologies.

Build cloud-native data solutions using AWS services including EMR S3 EC2 Lambda DynamoDB and

API Gateway.

Design and enhance Apache Airflow workflows including complex DAGs scheduling dependency

management monitoring and failure handling.

Optimize AWS EMR performance and cost efficiency across large-scale data workloads.

Participate in requirements gathering technical research and solution design.

Contribute to architecture reviews code reviews performance tuning and operational readiness.

Support testing validation and integration across applications and data pipelines.

Collaborate with product owners data engineers backend engineers QA and DevOps teams in an

Agile/Scrum environment.

Troubleshoot production issues and drive automation to improve system reliability.

All other duties as assigned.

Required Qualifications

6 years of hands-on experience building enterprise-scale applications data platforms or distributed systems.

6 years of experience developing and operating Big Data platforms in the cloud preferably using AWS EMR

and the Hadoop ecosystem.

Strong hands-on experience with AWS Spark Python and/or Scala Airflow SQL and Hive.

Advanced Python or Scala development skills with experience building production-grade data pipelines.
Strong experience with Apache Airflow orchestration for complex production workflows.

Solid understanding of data engineering concepts including batch processing data quality performance

optimisation and reliability.

Experience with Git Jenkins and CI/CD workflows.

Strong analytical problem-solving and communication skills.

Ability to work effectively in cross-functional Agile/Scrum teams.

Technical Skills

Required

AWS

AWS EMR

Apache Spark

Python

Scala

Apache Airflow

SQL

Apache Hive

Hadoop ecosystem

CI/CD

Git

Jenkins

Nice-to-have

LLMs

Generative AI

Agentic AI

API design

Microservices

Event-driven architectures

Serverless architectures

Infrastructure as code

Automated testing

Production deployment

Data governance

Metadata management

Data lineage

Data observability

Tools/Platforms

AWS EMR

Amazon S3

Amazon EC2

AWS Lambda

Amazon DynamoDB

Amazon API Gateway

Apache Spark

Apache Airflow

Apache Hive

Hadoop ecosystem

Git

Jenkins

Preferred Qualifications

Experience with LLMs Generative AI Agentic AI or AI-assisted engineering workflows.

Experience with API design microservices event-driven or serverless architectures.

Experience with infrastructure as code automated testing and production deployment.

Exposure to data governance metadata management lineage or data observability platforms.
Role Logistics

Location Type: onsite

Employment Type: Full-Time

Data Engineer (Mid) - 4777 IT Development Team Overview Location: onsite Hyderabad Employment Type: full time Experience: 6 years Compensation: INR- Interview Process: L1: Technical interview with Engineer (Virtual) L2: SME interview (Virtual) L3: Final round with Manager (Onsite)...

Data Engineer (Mid) - 4777

IT Development Team

Overview

Location: onsite Hyderabad

Employment Type: full time

Experience: 6 years

Compensation: INR-

Interview Process:

L1: Technical interview with Engineer (Virtual)

L2: SME interview (Virtual)

L3: Final round with Manager (Onsite)

Job Title

Data Engineer (Mid)

Experience Required

Extracted: 6 years of hands-on experience building enterprise-scale applications data platforms or

distributed systems.

Strong experience in Python (5 years)

Big Data (6 years)

Hands-on expertise with AWS services particularly:

EMR (mandatory and most critical skill)

EC2

Lambda

Candidate should have experience with EMR performance and cost optimization

Overview

Seeking a Data Engineer / Backend Developer to design build and operate cloud-native API-driven Big Data

systems. The role focuses on AWS EMR and Spark-based batch processing with strong emphasis on Python

development workflow orchestration (Airflow) and production reliability.

Key Responsibilities

Design and develop API-driven systems to govern manage and monitor large-scale batch Big Data

applications.

Build scalable backend services and data engineering solutions supporting data processing and operational

workflows.

Develop and maintain data transformation processes using Spark SQL Hive Python Scala and related

technologies.

Build cloud-native data solutions using AWS services including EMR S3 EC2 Lambda DynamoDB and

API Gateway.

Design and enhance Apache Airflow workflows including complex DAGs scheduling dependency

management monitoring and failure handling.

Optimize AWS EMR performance and cost efficiency across large-scale data workloads.

Participate in requirements gathering technical research and solution design.

Contribute to architecture reviews code reviews performance tuning and operational readiness.

Support testing validation and integration across applications and data pipelines.

Collaborate with product owners data engineers backend engineers QA and DevOps teams in an

Agile/Scrum environment.

Troubleshoot production issues and drive automation to improve system reliability.

All other duties as assigned.

Required Qualifications

6 years of hands-on experience building enterprise-scale applications data platforms or distributed systems.

6 years of experience developing and operating Big Data platforms in the cloud preferably using AWS EMR

and the Hadoop ecosystem.

Strong hands-on experience with AWS Spark Python and/or Scala Airflow SQL and Hive.

Advanced Python or Scala development skills with experience building production-grade data pipelines.
Strong experience with Apache Airflow orchestration for complex production workflows.

Solid understanding of data engineering concepts including batch processing data quality performance

optimisation and reliability.

Experience with Git Jenkins and CI/CD workflows.

Strong analytical problem-solving and communication skills.

Ability to work effectively in cross-functional Agile/Scrum teams.

Technical Skills

Required

AWS

AWS EMR

Apache Spark

Python

Scala

Apache Airflow

SQL

Apache Hive

Hadoop ecosystem

CI/CD

Git

Jenkins

Nice-to-have

LLMs

Generative AI

Agentic AI

API design

Microservices

Event-driven architectures

Serverless architectures

Infrastructure as code

Automated testing

Production deployment

Data governance

Metadata management

Data lineage

Data observability

Tools/Platforms

AWS EMR

Amazon S3

Amazon EC2

AWS Lambda

Amazon DynamoDB

Amazon API Gateway

Apache Spark

Apache Airflow

Apache Hive

Hadoop ecosystem

Git

Jenkins

Preferred Qualifications

Experience with LLMs Generative AI Agentic AI or AI-assisted engineering workflows.

Experience with API design microservices event-driven or serverless architectures.

Experience with infrastructure as code automated testing and production deployment.

Exposure to data governance metadata management lineage or data observability platforms.
Role Logistics

Location Type: onsite

Employment Type: Full-Time