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Cloud Data Engineer

Sydney, NS-Level37 TowerTwo, New South Wales, Australia

Actively hiring, first seen by us 1 day ago
Pay
Pay not listed
Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid remote
From the employer’s posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full-time
From the employer’s posting

What you’ll work on

Full posting

Results-driven Data Engineer with expertise in designing, building, and optimizing scalable data pipelines across cloud and distributed systems.

Skills/Tools: Py-spark, Spark SQL, SAS, Databricks, Java, Python, Power Bi, Qlikview, Automation (RPA), web-scraping, IBM Sterling

  • Build and maintain scalable data pipelines using cloud services

  • Develop data products that unify customer data from multiple sources

  • Write PySpark and Spark SQL scripts for complex data transformations

  • Monitor data platforms, respond to alerts, and cut pipeline costs

  • Perform root cause analysis on job failures and ensure stability after releases

From the employer’s posting
Results-driven Data Engineer with expertise in designing, building, and optimizing scalable data pipelines across cloud and distributed systems. Skilled in Python, PySpark, and SQL for data ingestion, transformation, and integration, with a strong focus on improving efficiency, reducing costs, and ensuring data quality. Experienced in metadata-driven frameworks, ETL process enhancements, and governance practices to deliver clean, reliable data for analytics and reporting. Adept at collaborating with cross-functional teams, monitoring platform performance, and making continuous improvements to support business growth and decision-making.
Skills/Tools: Py-spark, Spark SQL, SAS, Databricks, Java, Python, Power Bi, Qlikview, Automation (RPA), web-scraping, IBM Sterling
Build and maintain scalable data pipelines using cloud services for ingestion, transformation, and storage.
Develop data products that integrate customer data from multiple sources into unified profiles.
Write Pyspark, and Spark SQL scripts to perform complex data transformations
Monitor data platforms, respond to alerts, and optimize pipelines for efficiency and cost reduction.
Perform root cause analysis (RCA) for job failures and ensure stability after releases.

What you’ll bring

All qualifications

Core experience

  • Skills in Python, PySpark, and SQL for pipelines
  • Experience with Databricks and Azure or AWS cloud services
  • Experience with Control-M or Databricks workflows for job scheduling
  • Understanding of security best practices and compliance requirements
  • Banking domain knowledge in Basel 4 and regulatory reporting
Qualification wording
Skilled in Python, PySpark, and SQL for data ingestion, transformation, and integration
Cloud Platform: Azure services, Databricks, AWS
Job Scheduler: Control-M, DataBricks workflows
Understanding of security best practices and compliance requirements
Banking: Basel 4, Regulatory Reporting
Apply at Cognizant

Posting record

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 3, 20261 day ago
Recorded sightings
2
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 1

Early. Similar jobs usually come down between day 5 and day 54.

From 10,736 similar postings that came down. Coming down is not always a hire.

Cognizant is hiring

140 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down quickly
  • 4% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Java
  • Python
  • SAS
  • SQL
  • AWS
  • Azure
  • Databricks
  • Oracle
  • Power BI
  • Spark
  • PySpark
Where the posting names them
Mandatory Skills - Skills/Tools: Py-spark, Spark SQL, SAS, Databricks, Java, Python, Power Bi, Qlikview, Automation (RPA), web-scraping, IBM Sterling - Database: Hive, Oracle, SSMS, etc
- Cloud Platform: Azure services, Databricks, AWS - Language: Python, Java - Ci/CD Tools: Bitbucket, Github and Jenkins
Position Summary Results-driven Data Engineer with expertise in designing, building, and optimizing scalable data pipelines across cloud and distributed systems. Skilled in Python, PySpark, and SQL for data ingestion, transformation, and integration, with a strong focus on improving efficiency, reducing costs, and ensuring data quality. Experienced in metadata-driven frameworks, ETL process enhancements, and governance practices to deliver clean, reliable data for analytics and reporting. Adept at collaborating with cross-functional teams, monitoring platform performance, and making continuous improvements to support business growth and decision-making. Mandatory Skills
SQL (Advance) - HackerRank Python (Basic) – HackerRank Salary Range: 90k-100k
- Create metadata-driven frameworks to ensure data quality, consistency, and governance. - Write Pyspark, and Spark SQL scripts to perform complex data transformations, ensuring data pipelines are efficient, scalable, and optimized for analytics and reporting. - Support ETL processes by fixing errors, improving resiliency, and ensuring data integrity across reports and dashboards.
Databricks Certified Data Engineer Associate SQL (Advance) - HackerRank Python (Basic) – HackerRank
- Database: Hive, Oracle, SSMS, etc - Cloud Platform: Azure services, Databricks, AWS - Language: Python, Java
- Ci/CD Tools: Bitbucket, Github and Jenkins - Job Scheduler: Control-M, DataBricks workflows - Monitoring and Logging: Skills in using monitoring tools and analysing the root cause using Spark Logs
Qualifications/Certifications Databricks Certified Data Engineer Associate SQL (Advance) - HackerRank
- Skills/Tools: Py-spark, Spark SQL, SAS, Databricks, Java, Python, Power Bi, Qlikview, Automation (RPA), web-scraping, IBM Sterling - Database: Hive, Oracle, SSMS, etc - Cloud Platform: Azure services, Databricks, AWS
- Job Scheduler: Control-M, DataBricks workflows - Monitoring and Logging: Skills in using monitoring tools and analysing the root cause using Spark Logs - Security and Compliance: Understanding of security best practices and compliance requirements

Your next step

Complete your application on careers.cognizant.com. The employer’s form will show what is required.

Already applied? Track this application

Has Cognizant posted this job before?

Yes. We’ve followed one other Cloud Data Engineer job there since November 2026. It is still up.

  1. SydneyStill up after 1 day, first seen Nov 3
  2. This jobUp 1 day so far, first seen Nov 3

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

What makes Cognizant a unique place to work? The combination of rapid growth and an unique place international and innovative environment! This is creating many opportunities for people like YOU — people with an entrepreneurial spirit who want to make a difference in this world.

At Cognizant, together with your colleagues from all around the world, you will collaborate on creating solutions for the world's leading companies and help them become more flexible, more innovative, and successful. Moreover, this is your chance to be part of the success story.

Position Summary

Results-driven Data Engineer with expertise in designing, building, and optimizing scalable data pipelines across cloud and distributed systems. Skilled in Python, PySpark, and SQL for data ingestion, transformation, and integration, with a strong focus on improving efficiency, reducing costs, and ensuring data quality. Experienced in metadata-driven frameworks, ETL process enhancements, and governance practices to deliver clean, reliable data for analytics and reporting. Adept at collaborating with cross-functional teams, monitoring platform performance, and making continuous improvements to support business growth and decision-making.

Mandatory Skills

  • Skills/Tools: Py-spark, Spark SQL, SAS, Databricks, Java, Python, Power Bi, Qlikview, Automation (RPA), web-scraping, IBM Sterling
  • Database: Hive, Oracle, SSMS, etc
  • Cloud Platform: Azure services, Databricks, AWS
  • Language: Python, Java
  • Ci/CD Tools: Bitbucket, Github and Jenkins
  • Job Scheduler: Control-M, DataBricks workflows
  • Monitoring and Logging: Skills in using monitoring tools and analysing the root cause using Spark Logs
  • Security and Compliance: Understanding of security best practices and compliance requirements
  • Business Domain Knowledge: Banking: Basel 4, Regulatory Reporting

Roles And Responsibilities

  • Build and maintain scalable data pipelines using cloud services for ingestion, transformation, and storage.
  • Develop data products that integrate customer data from multiple sources into unified profiles.
  • Create metadata-driven frameworks to ensure data quality, consistency, and governance.
  • Write Pyspark, and Spark SQL scripts to perform complex data transformations, ensuring data pipelines are efficient, scalable, and optimized for analytics and reporting.
  • Support ETL processes by fixing errors, improving resiliency, and ensuring data integrity across reports and dashboards.
  • Monitor data platforms, respond to alerts, and optimize pipelines for efficiency and cost reduction.
  • Perform root cause analysis (RCA) for job failures and ensure stability after releases.
  • Collaborate with onsite and offshore teams to coordinate tasks, align processes, and deliver projects smoothly.
  • Participate in design reviews, implementation walkthroughs, and production deployments.
  • Apply governance best practices to maintain security, lineage, and compliance with organizational and regulatory standards.
  • Work closely with stakeholders and architects to capture requirements and deliver reliable solutions.
  • Use Atlassian tools (Jira, Confluence, Bitbucket) for project management, documentation, and collaboration.
  • Lead projects through effective planning, prioritization, and team coordination to ensure successful delivery.

Qualifications/Certifications

Databricks Certified Data Engineer Associate

SQL (Advance) - HackerRank

Python (Basic) – HackerRank

Salary Range: 90k-100k

Date of Posting: 3/11/2026

Next Steps: If you feel this opportunity suits you, or Cognizant is the type of organization you would like to join, we want to have a conversation with you! Please apply directly with us.

For a complete list of open opportunities with Cognizant, visit http://www.cognizant.com/careers. Cognizant is committed to providing Equal Employment Opportunities. Successful candidates will be required to undergo a background check.

Source details

View original posting ↗

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Location & working pattern

Sydney, NS-Level37 TowerTwo, New South Wales, Australia

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