Lead II - SE - AWS, Apache Spark (PySpark/Scala), Apache Kafka
at Global digital transformation solutions provider.
Amazon Web Services (AWS)
Scala
Jenkins
Data Analytics
Data Science
Java
MongoDBJOB 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.
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