2+ DMS Jobs in Hyderabad | DMS Job openings in Hyderabad

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

1. 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.

1. 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.

1. Data Frameworks

• Strong knowledge of Spark DataFrames and Datasets.

1. ETL Pipeline Development

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

1. Database Modeling & Data Warehousing

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

1. 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.

1. 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.

AWS Glue Developer 

Work Experience: 6 to 8 Years

Work Location:  Noida, Bangalore, Chennai & Hyderabad

Must Have Skills: AWS Glue, DMS, SQL, Python, PySpark, Data integrations and Data Ops, 

Job Reference ID:BT/F21/IND

Job Description:

Design, build and configure applications to meet business process and application requirements.

Responsibilities:

7 years of work experience with ETL, Data Modelling, and Data Architecture Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark Extensive experience to build data platforms on AWS using core AWS services Step function, EMR, Lambda, Glue and Athena, Redshift, Postgres, RDS etc and design/develop data engineering solutions. Orchestrate using Airflow.

Technical Experience:

Hands-on experience on developing Data platform and its components Data Lake, cloud Datawarehouse, APIs, Batch and streaming data pipeline Experience with building data pipelines and applications to stream and process large datasets at low latencies.

➢ Enhancements, new development, defect resolution and production support of Big data ETL development using AWS native services.

➢ Create data pipeline architecture by designing and implementing data ingestion solutions.

➢ Integrate data sets using AWS services such as Glue, Lambda functions/ Airflow.

➢ Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, RDS, S3, Athena.

➢ Author ETL processes using Python, Pyspark.

➢ Build Redshift Spectrum direct transformations and data modelling using data in S3.

➢ ETL process monitoring using CloudWatch events.

➢ You will be working in collaboration with other teams. Good communication must.

➢ Must have experience in using AWS services API, AWS CLI and SDK

Professional Attributes:

➢ Experience operating very large data warehouses or data lakes Expert-level skills in writing and optimizing SQL Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technology.

➢ Must have 6+ years of big data ETL experience using Python, S3, Lambda, Dynamo DB, Athena, Glue in AWS environment.

➢ Expertise in S3, RDS, Redshift, Kinesis, EC2 clusters highly desired.

Qualification:

➢ Degree in Computer Science, Computer Engineering or equivalent.

Salary: Commensurate with experience and demonstrated competence