Lead II - SE - AWS, Apache Spark (PySpark/Scala), Apache Kafka

Global digital transformation solutions provider.

Lead II - SE - AWS, Apache Spark (PySpark/Scala), Apache Kafka

Peak Hire Solutions

Company

Home

Lead II - SE - AWS, Apache Spark (PySpark/Scala), Apache Kafka

at Global digital transformation solutions provider.

Agency job

via Peak Hire Solutions

5 - 8 yrs

₹11L - ₹20L / yr

Hyderabad

Skills

PySpark

Apache Kafka

Data architecture

Amazon Web Services (AWS)

EMR

Apache Airflow

Amazon S3

DMS

Amazon EC2

Scala

Apache Spark

Spark

ETL

CI/CD

Jenkins

Big Data

SQL

Database modeling

OLAP

OLTP

Data Analytics

Automation

Automated testing

Workflow

Data engineering

Data security

HIPAA

Data Science

Datawarehousing

Java

NOSQL Databases

DynamoDB

Cassandra

MongoDB

Data governance

Splunk

Dynatrace

JOB DETAILS:

* Job Title: Lead II - Software Engineering - AWS, Apache Spark (PySpark/Scala), Apache Kafka

* Industry: Global digital transformation solutions provider

* Salary: Best in Industry

* Experience: 5-8 years

* Location: Hyderabad

Job Summary

We are seeking a skilled Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data platforms. The role involves working with large-scale batch and real-time data processing systems, collaborating with cross-functional teams, and ensuring data reliability, security, and performance across the data lifecycle.

Key Responsibilities

ETL Pipeline Development & Optimization

Design, develop, and maintain complex end-to-end ETL pipelines for large-scale data ingestion and processing.
Optimize data pipelines for performance, scalability, fault tolerance, and reliability.

Big Data Processing

Develop and optimize batch and real-time data processing solutions using Apache Spark (PySpark/Scala) and Apache Kafka.
Ensure fault-tolerant, scalable, and high-performance data processing systems.

Cloud Infrastructure Development

Build and manage scalable, cloud-native data infrastructure on AWS.
Design resilient and cost-efficient data pipelines adaptable to varying data volume and formats.

Real-Time & Batch Data Integration

Enable seamless ingestion and processing of real-time streaming and batch data sources (e.g., AWS MSK).
Ensure consistency, data quality, and a unified view across multiple data sources and formats.

Data Analysis & Insights

Partner with business teams and data scientists to understand data requirements.
Perform in-depth data analysis to identify trends, patterns, and anomalies.
Deliver high-quality datasets and present actionable insights to stakeholders.

CI/CD & Automation

Implement and maintain CI/CD pipelines using Jenkins or similar tools.
Automate testing, deployment, and monitoring to ensure smooth production releases.

Data Security & Compliance

Collaborate with security teams to ensure compliance with organizational and regulatory standards (e.g., GDPR, HIPAA).
Implement data governance practices ensuring data integrity, security, and traceability.

Troubleshooting & Performance Tuning

Identify and resolve performance bottlenecks in data pipelines.
Apply best practices for monitoring, tuning, and optimizing data ingestion and storage.

Collaboration & Cross-Functional Work

Work closely with engineers, data scientists, product managers, and business stakeholders.
Participate in agile ceremonies, sprint planning, and architectural discussions.

Skills & Qualifications

Mandatory (Must-Have) Skills

AWS Expertise

Hands-on experience with AWS Big Data services such as EMR, Managed Apache Airflow, Glue, S3, DMS, MSK, and EC2.
Strong understanding of cloud-native data architectures.

Big Data Technologies

Proficiency in PySpark or Scala Spark and SQL for large-scale data transformation and analysis.
Experience with Apache Spark and Apache Kafka in production environments.

Data Frameworks

Strong knowledge of Spark DataFrames and Datasets.

ETL Pipeline Development

Proven experience in building scalable and reliable ETL pipelines for both batch and real-time data processing.

Database Modeling & Data Warehousing

Expertise in designing scalable data models for OLAP and OLTP systems.

Data Analysis & Insights

Ability to perform complex data analysis and extract actionable business insights.
Strong analytical and problem-solving skills with a data-driven mindset.

CI/CD & Automation

Basic to intermediate experience with CI/CD pipelines using Jenkins or similar tools.
Familiarity with automated testing and deployment workflows.

Good-to-Have (Preferred) Skills

Knowledge of Java for data processing applications.
Experience with NoSQL databases (e.g., DynamoDB, Cassandra, MongoDB).
Familiarity with data governance frameworks and compliance tooling.
Experience with monitoring and observability tools such as AWS CloudWatch, Splunk, or Dynatrace.
Exposure to cost optimization strategies for large-scale cloud data platforms.

Skills: big data, scala spark, apache spark, ETL pipeline development

******

Notice period - 0 to 15 days only

Job stability is mandatory

Location: Hyderabad

Note: If a candidate is a short joiner, based in Hyderabad, and fits within the approved budget, we will proceed with an offer

F2F Interview: 14th Feb 2026

3 days in office, Hybrid model.

JOB DETAILS:

* Job Title: Lead II - Software Engineering - AWS, Apache Spark (PySpark/Scala), Apache Kafka

* Industry: Global digital transformation solutions provider

* Salary: Best in Industry

* Experience: 5-8 years

* Location: Hyderabad

Job Summary

Key Responsibilities

ETL Pipeline Development & Optimization

Design, develop, and maintain complex end-to-end ETL pipelines for large-scale data ingestion and processing.
Optimize data pipelines for performance, scalability, fault tolerance, and reliability.

Big Data Processing

Develop and optimize batch and real-time data processing solutions using Apache Spark (PySpark/Scala) and Apache Kafka.
Ensure fault-tolerant, scalable, and high-performance data processing systems.

Cloud Infrastructure Development

Build and manage scalable, cloud-native data infrastructure on AWS.
Design resilient and cost-efficient data pipelines adaptable to varying data volume and formats.

Real-Time & Batch Data Integration

Enable seamless ingestion and processing of real-time streaming and batch data sources (e.g., AWS MSK).
Ensure consistency, data quality, and a unified view across multiple data sources and formats.

Data Analysis & Insights

Partner with business teams and data scientists to understand data requirements.
Perform in-depth data analysis to identify trends, patterns, and anomalies.
Deliver high-quality datasets and present actionable insights to stakeholders.

CI/CD & Automation

Implement and maintain CI/CD pipelines using Jenkins or similar tools.
Automate testing, deployment, and monitoring to ensure smooth production releases.

Data Security & Compliance

Collaborate with security teams to ensure compliance with organizational and regulatory standards (e.g., GDPR, HIPAA).
Implement data governance practices ensuring data integrity, security, and traceability.

Troubleshooting & Performance Tuning

Identify and resolve performance bottlenecks in data pipelines.
Apply best practices for monitoring, tuning, and optimizing data ingestion and storage.

Collaboration & Cross-Functional Work

Work closely with engineers, data scientists, product managers, and business stakeholders.
Participate in agile ceremonies, sprint planning, and architectural discussions.

Skills & Qualifications

Mandatory (Must-Have) Skills

AWS Expertise

Hands-on experience with AWS Big Data services such as EMR, Managed Apache Airflow, Glue, S3, DMS, MSK, and EC2.
Strong understanding of cloud-native data architectures.

Big Data Technologies

Proficiency in PySpark or Scala Spark and SQL for large-scale data transformation and analysis.
Experience with Apache Spark and Apache Kafka in production environments.

Data Frameworks

Strong knowledge of Spark DataFrames and Datasets.

ETL Pipeline Development

Proven experience in building scalable and reliable ETL pipelines for both batch and real-time data processing.

Database Modeling & Data Warehousing

Expertise in designing scalable data models for OLAP and OLTP systems.

Data Analysis & Insights

Ability to perform complex data analysis and extract actionable business insights.
Strong analytical and problem-solving skills with a data-driven mindset.

CI/CD & Automation

Basic to intermediate experience with CI/CD pipelines using Jenkins or similar tools.
Familiarity with automated testing and deployment workflows.

Good-to-Have (Preferred) Skills

Knowledge of Java for data processing applications.
Experience with NoSQL databases (e.g., DynamoDB, Cassandra, MongoDB).
Familiarity with data governance frameworks and compliance tooling.
Experience with monitoring and observability tools such as AWS CloudWatch, Splunk, or Dynatrace.
Exposure to cost optimization strategies for large-scale cloud data platforms.

Skills: big data, scala spark, apache spark, ETL pipeline development

******

Notice period - 0 to 15 days only

Job stability is mandatory

Location: Hyderabad

Note: If a candidate is a short joiner, based in Hyderabad, and fits within the approved budget, we will proceed with an offer

F2F Interview: 14th Feb 2026

3 days in office, Hybrid model.

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