Cognizant is looking for a
Data Engineer – Databricks
in developing customized product for our clients. The role is expected to drive technology discussions and analyze the current landscape for gaps in addressing business needs. Cognizant needs a motivated individual to challenge the status quo and provide thought leadership/best practices to enhance our current services and technologies.
Job Title: Data Engineer – Databricks
Location: Sydney,AU
Duration : Full Time
Responsibilities:
An exciting opportunity has become available for a
Data Engineer – Databricks
to join Cognizant’s Data Services team. Reporting to the Data Services Lead, this role is pivotal in supporting the development and evolution of our data and analytics platform. You will play a key role in designing scalable data solutions, enabling data-driven decision-making across the business, and providing technical guidance to cross-functional teams during a period of transformation and growth.
Key Responsibilities:
Design and develop scalable data engineering assets and feature engineering frameworks.
Build and maintain robust data pipelines using Python, Databricks, Spark, and Azure technologies.
Develop ETL solutions to integrate data from multiple sources into the analytics platform.
Implement Azure Data Factory frameworks to support data migration and new project delivery.
Expand platform capabilities by identifying and integrating new data sources.
Automate manual processes and optimize data delivery for scalability and efficiency.
Conduct peer code reviews and foster a DevOps culture within the team.
Ensure data integrity and accuracy across reports and dashboards.
Provide technical guidance and advisory support to business units.
Contribute to the development of a best-practice data and analytics platform using next-gen technologies.
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Experience \& Qualifications:
To be successful in this role, you skills and experience should include:
Strong experience in MSBI/SSAS and Azure Data \& Analytics services.
Proven expertise in Azure Data Factory, Databricks, Azure Data Lake, and related technologies.
Experience building data pipelines across diverse systems including Azure SQL DB, ADLS Gen2, and Delta Lake.
Demonstrated leadership in managing data teams and projects.
Passion for learning and applying new data tools and best practices.
Experience working in Agile environments, both independently and in teams.
Excellent communication and stakeholder engagement skills.
Deep understanding of the data management lifecycle and data quality practices.
Familiarity with tools and technologies such as Power BI, SQL Server, SSIS, SSRS, MongoDB, Graph databases, R, Python, Spark, GitHub, Jira, and Confluence.