[Skip to main content](#main-content) [OpenNash Jobs](https://jobs.opennash.com/) [Hiring report](/reports/hiring/) · [All Tata Consultancy Services jobs](https://jobs.opennash.com/companies/tata-consultancy-services/) · [Search jobs](/search/) Tata Consultancy Services · Sydney # Senior Data Engineer Sydney Senior individual contributor Data & Analytics Last seen on Tata Consultancy Services’s official careers site on August 1, 2026; it may have closed since. [Apply on Tata Consultancy Services’s careers site →](https://ibegin.tcsapps.com/candidate/jobs/422253J) [OpenNash Jobs](https://jobs.opennash.com/) / [Tata Consultancy Services](https://jobs.opennash.com/companies/tata-consultancy-services/) / Senior Data Engineer ## Job description ### Job Description AWS SageMaker Unified Studio Expertise: Proficiency with AWS SageMaker Unified Studio, including its various components Discover, Build and Govern. Experience with development in Sagemaker IDE and Application (Jupyterlab, Spaces and Partner AI Apps). Data Analysis and Integrations ( Query Editor, Visual ETL Jobs and Data Processing jobs) Orchestration of workflows and ML Pipelines Understanding and expertise to work with ML and Gen AI tools available in unified studio are ad-on values. Setting up projects and data governance in SageMaker Unified studio Advanced Data Ingestion & Processing (Real-time & Batch): Framework Development: Proven ability to design, develop, and implement highly reusable and adaptable data ingestion frameworks capable of handling diverse source types (e.g., databases, APIs, message queues, file systems). ### Low-Latency Real-time Deep expertise in building real-time data pipelines with stringent sub-second latency requirements, utilising services like AWS Kinesis (Data Streams/Firehose), Apache Kafka, or similar streaming technologies. ### Batch Processing Experience with robust batch ingestion patterns and tools (e.g., AWS Glue, Apache Spark) for efficient processing of larger datasets. ### Data Transformation Stron g skills in designing and implementing efficient data transformation logic for both streaming and batch data. ### Programming and Scripting Advanced proficiency in Python, particularly for developing scalable data ingestion and export frameworks, API integration, and extensive use of the AWS SDK (Boto3). Experience with performance optimisation techniques for Python applications in data-intensive environments. Familiarity with other relevant languages (e.g., Scala, Spark) for high-performance streaming applications is beneficial. ### AWS Services for Data and Infrastructure In-depth knowledge of core AWS services: Lambda, S3, DynamoDB, CloudWatch, SQS, SNS, and API Gateway. Strong understanding of AWS networking (VPC, security groups, private endpoints) and IAM for secure, fine-grained access control. ### Key Skillset Previous experience in developing framework for batch and real time data ingestions in relation and no-sql databases or filesystems. Previous experience in Real time data ingestion with low latency with experience on AWS Kinesis Stream, Apache Kafka or similar streaming technologies Proven experience in various database technologies (e.g. Oracle, Teradata, MongoDB, Snowflake etc) Sound knowledge and experience in building Data Warehouses and Data Lakehouses. Data Modeling experience is a plus point