Sydney, NS-Level37 TowerTwo, New South Wales, Australia
Actively hiring, first seen by us 6 hours agoWork setup in the employer’s posting: hybrid remoteFrom the employer’s posting
Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Design, develop and maintain scalable data pipelines across PySpark, Synapse, PowerCenter and IICS
Build batch and near-real-time integration for structured and large-volume datasets
Troubleshoot production data failures, find root causes and tune jobs
Develop and optimize Spark transformations and performance tuning
Run data validation, reconciliation and data quality checks
Design, develop, and maintain scalable data pipelines using PySpark, SQL, Azure Synapse, Informatica PowerCenter, and IICS.
Build batch and near-real-time data integration solutions for structured, semi-structured, and large-volume datasets.
Troubleshoot production issues, identify root causes, optimize jobs, and ensure timely resolution of data processing failures.
Develop and optimize Spark-based transformations using PySpark, Spark SQL, DataFrames, partitioning, caching, and performance tuning techniques.
Perform data analysis, data profiling, validation, reconciliation, and data quality checks to ensure accuracy and completeness of data pipelines.
SQL: Advanced SQL skills including complex joins, analytical functions, query optimization, stored procedures, views, data validation, and reconciliation.
From the employer’s posting.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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143 open jobs
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Job Summary: We are looking for a technically strong Senior Data Engineer with 8 to 15 years of experience in designing, developing, and supporting enterprise-scale data engineering solutions. The role requires a strong combination of PySpark, Azure Synapse, Informatica PowerCenter, Informatica Intelligent Cloud Services (IICS), and SQL skills. The candidate must have hands-on experience in building scalable data pipelines, integrating data across cloud and on-premise platforms, and delivering reliable, performance-optimized data solutions. Responsibilities:
Responsibilities: - Design, develop, and maintain scalable data pipelines using PySpark, SQL, Azure Synapse, Informatica PowerCenter, and IICS. - Build batch and near-real-time data integration solutions for structured, semi-structured, and large-volume datasets.
- Build batch and near-real-time data integration solutions for structured, semi-structured, and large-volume datasets. - Develop and optimize Spark-based transformations using PySpark, Spark SQL, DataFrames, partitioning, caching, and performance tuning techniques. - Work on Azure Synapse Analytics for data warehousing, pipeline orchestration, transformation logic, and analytics-ready data processing.
- Develop and support IICS assets including mappings, mapping tasks, taskflows, connections, schedules, and cloud data integration processes. - Write complex SQL queries, stored procedures, views, and performance-optimized data transformation logic across relational databases and cloud data platforms. - Perform data analysis, data profiling, validation, reconciliation, and data quality checks to ensure accuracy and completeness of data pipelines.
Required Skills: - PySpark: Strong hands-on experience in developing distributed data processing pipelines, transformations, Spark SQL logic, and performance-tuned Spark jobs. - Azure Synapse: Hands-on experience with Synapse Pipelines, Synapse SQL, Spark Pools, notebooks, linked services, and integration with Azure data storage.
- PySpark: Strong hands-on experience in developing distributed data processing pipelines, transformations, Spark SQL logic, and performance-tuned Spark jobs. - Azure Synapse: Hands-on experience with Synapse Pipelines, Synapse SQL, Spark Pools, notebooks, linked services, and integration with Azure data storage. - Informatica PowerCenter: Strong development experience in mappings, sessions, workflows, transformations, parameterization, scheduling, troubleshooting, and performance tuning.
- IICS: Hands-on experience in Informatica Cloud Data Integration, mappings, mapping tasks, taskflows, connectors, schedules, monitoring, and error handling. - SQL: Advanced SQL skills including complex joins, analytical functions, query optimization, stored procedures, views, data validation, and reconciliation. - Data Engineering: Strong understanding of ETL/ELT design, data warehousing, data lake concepts, data modeling, ingestion patterns, and pipeline orchestration.
- Develop and optimize Spark-based transformations using PySpark, Spark SQL, DataFrames, partitioning, caching, and performance tuning techniques. - Work on Azure Synapse Analytics for data warehousing, pipeline orchestration, transformation logic, and analytics-ready data processing. - Design, develop, and maintain Informatica PowerCenter mappings, sessions, workflows, reusable transformations, parameter files, and deployment objects.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
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.
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.
Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industry and business process expertise, and a global, collaborative workforce that embodies the future of work. Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500 and is ranked among the top performing and fastest growing companies in the world.
Our Culture:
Your passion, integrity and experience are integral to Cognizant's success. You will join a dynamic and expanding global leader in IT and Business consultancy where you will be valued for who you are. We take pride in our partnership with our clients, so your ability to add value and provide exceptional service to our clients is fundamental to your success. In return, you will be presented with opportunities to develop your career and collaborate with talented colleagues in a supportive, diverse environment.
At Cognizant we recognize that companies that are open and welcoming to a multi-culturally diverse workforce will thrive with fresh perspectives and collaborative knowledge. Cognizant focuses on promoting & increasing gender diversity and providing a workplace which encourages great participation and an equal playing field, where merit and accomplishment are the only criteria for success.
Job Summary:
We are looking for a technically strong Senior Data Engineer with 8 to 15 years of experience in designing, developing, and supporting enterprise-scale data engineering solutions. The role requires a strong combination of PySpark, Azure Synapse, Informatica PowerCenter, Informatica Intelligent Cloud Services (IICS), and SQL skills. The candidate must have hands-on experience in building scalable data pipelines, integrating data across cloud and on-premise platforms, and delivering reliable, performance-optimized data solutions.
Responsibilities:
Required Skills:
Benefits:
Joining Cognizant will give you the opportunity to learn and collaborate with some of the most talented people in the industry, while having your finger on the pulse of emerging industry trends and working on the cutting edge of technology in your field of expertise.
We recognize that our people perform at their best when they feel valued as significant contributors and that is why at Cognizant, taking care of our employees is a priority:
· You can pursue innovative career tracks and opportunities here
· You can enhance your professional development through education and dedicated training
· We’ll give you the skills you need to keep pace with the changing workplace while our compensation, benefits and wellness packages help you stay healthy and plan for the future.
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Sydney, NS-Level37 TowerTwo, New South Wales, Australia
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