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Data Engineering

Unisys CORP - Bangalore, KA, India

Posted Jun 4, 2026

Benefits

Parental leave
Not verified
Non-birth-parent leave
Not verified
Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
Not verified
Childcare support
Not verified
Learning budget
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Verification
Not verified checked Jun 13, 2026
Salary
Not verified
401(k) match
Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Data From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
Not verified

Company

Company stage
Public-company From the posting source checked Jun 20, 2026
Equity
Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter
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Assessment
Not verified
Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Engineering Bangalore, KA, India Bangalore, KA, India What success looks like in this role: End-to-End Pipeline Engineering: Build and automate robust ETL/ELT pipelines using Azure Data Factory (ADF), AWS Glue, and Apache Airflow. · Distributed Computing: Develop large-scale data processing jobs using PySpark and Scala within Databricks or EMR environments. · Streaming & Real-time Integration: Design and implement real-time data ingestion and processing layers using Apache Kafka, Confluent, or AWS Kinesis. · Data Lakehouse : Manage and optimize cloud storage using ADLS Gen2 and S3, implementing ACID transactions with Delta Lake or Apache Iceberg. · Advanced Data Modeling: Design highly performant schemas for cloud data warehouses like Snowflake, Amazon Redshift, or Google BigQuery. · Data Transformation & Quality: Use dbt (data build tool) for modeling and implement automated quality checks using Great Expectations or Soda. · Infrastructure & CI/CD: Deploy and manage data infrastructure using Terraform or CloudFormation, and maintain CI/CD pipelines via GitHub Actions or GitLab CI. Technical Stack Requirements · Cloud Platforms: Deep hands-on experience with Microsoft Azure (ADF, Synapse, Databricks) and AWS (S3, Glue, Athena, Lambda). · Programming: Strong proficiency in Python (PySpark, FastAPI), SQL, and familiarity with Java or Scala. · Big Data Tools: Experience with Apache Spark, Apache Flink, and Hadoop ecosystem. · Databases: Strong knowledge of both Relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, or DynamoDB) databases. · Containerization: Proficiency with Docker and Kubernetes (K8s) for deploying data services. · Observability: Familiarity with monitoring tools like Prometheus, Grafana, or Datadog to track pipeline

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Apply link verified; last checked Aug 3, 2026.

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