We are seeking an experienced Senior Data Engineer to design, build, and maintain scalable data platforms and data processing pipelines. The ideal candidate will have strong expertise in Python, PySpark, AWS, DynamoDB, and OpenSearch , along with exposure to Java . This role requires hands-on experience building cloud-native big data solutions, optimizing large-scale data processing workloads, and enabling data-driven decision-making across the organization.

Design, develop, and maintain large-scale data pipelines using Python and PySpark.

Build and optimize batch and near real-time data processing solutions.

Design scalable data architectures on AWS.

Develop ETL/ELT workflows for ingesting, transforming, and publishing datasets.

Work with structured and semi-structured data from multiple sources.

Design and maintain NoSQL database solutions using DynamoDB.

Optimize data processing jobs for performance, scalability, and cost efficiency.

Collaborate with product teams, architects, and software engineers to define data requirements.

Monitor, troubleshoot, and resolve data platform and pipeline issues.

Implement data quality, governance, security, and observability best practices.

Data Engineering

Strong expertise in Python.

Extensive experience with PySpark and distributed data processing.

Hands-on experience building data lakes and modern data platforms.

Strong understanding of ETL/ELT frameworks and data modeling.

Experience processing large datasets efficiently.

AWS Cloud

Expert-level Knowledge Of AWS Services Such As

EMR

Databases

Strong SQL skills and query optimization experience.

Experience with NoSQL databases, particularly DynamoDB.

Understanding of partitioning, indexing, and data access patterns.

Hands-on experience with OpenSearch / Elasticsearch.





Experience designing indexes and search schemas.

Knowledge of query optimization and search performance tuning.

Experience implementing analytics and monitoring dashboards.

Programming

Strong Python development skills.

Working knowledge of Java.

Understanding of object-oriented programming and software engineering best practices.

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

- 8+ years of experience in Data Engineering.
- Experience with streaming platforms such as Kafka or Kinesis.
- Experience with Airflow or other workflow orchestration tools.
- Experience with Docker and Kubernetes.
- Exposure to Data Lake and Lakehouse architecture.
- Experience in Agile/Scrum development environments.

Snowflake

Machine Learning data pipelines

Ability to work in a quick-paced, cloud-native environment.

BA/BS degree and 8-10 years' relevant experience OR equivalent combination of education and experience

Unisys is proud to be an equal opportunity employer that considers all qualified applicants without regard to age, blood type, caste, citizenship, color, disability, family medical history, family status, ethnicity, gender, gender expression, gender identity, genetic information, marital status, national origin, parental status, pregnancy, race, religion, sex, sexual orientation, transgender status, veteran status or any other category protected by law.

Local employment practices and rights may vary by jurisdiction and are subject to applicable local laws. If you are a US job seeker unable to review the job opportunities herein, or cannot otherwise complete your expression of interest, without additional assistance and would like to discuss a request for reasonable accommodation, please contact our Global Recruiting organization at [HIDDEN TEXT] .

📌 (Senior) Data Engineer (ML, Big Data)
🏢 Unisys
📍 Secunderabad