About Us:
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 56 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the businesses with agile digital at scale to deliver unprecedented levels of performance and customer satisfaction. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.
Visit www.infosys.com to see how Infosys (NYSE: INFY) can help your enterprise navigate your next.
Role Description: Infosys is seeking a highly skilled and motivated Senior Consultant to join our DNA team. As a Senior Consultant you will be responsible for delivering high-quality data solutions, build and maintain an entire data stack that includes a wide variety of integrations that ingest data, a data warehouse, a pipeline of data transformations, and several services that push data into other tools. You will also be responsible for building resilient, secure high-performance infrastructure required for optimal ETL/ELT processes from a wide variety of data sources using SQL, data lake, databricks technologies, and contributing to high-end innovative technological solutions with the client to develop data and AI led initiatives for transformation. You would be involved in the execution and delivery of such engagements, playing a key role.
Location: Sydney
Salary: AUD 108,571- 119,893 Annual Gross
Please Note: - The above salary range is only indicative and maybe subject to suitable enhancements, based on internal company processes
Flexible working arrangements (hybrid, reviewed case-by-case basis). Feel free to connect with your recruiter to learn more about how this works in practice.
Roles and Responsibilities:

• Excellent hands-on development experience in data engineering, data storage, analytics, and visualization tools and technologies
• Expertise in various technologies and methodologies to create efficient data pipelines, optimize data storage, processing and accessibility.
• Work with data scientists, analysts, and business stakeholders to understand data requirements, develop and deliver data-driven solutions.
• Designing, building, and maintaining scalable and reliable data pipelines for extracting, transforming, and loading (ETL/ELT) data from various sources into data warehouses and data lakes.
• Defining and implementing data models, schemas, and architectures that ensure data quality, consistency, optimal performance, integrity and availability.
• Experience in ETL process implementation, data warehousing, and potentially deploying machine learning models.
• Experience in data modeling principles and data architecture design
• Ability to identify and resolve complex data-related issues, analyze performance bottlenecks, develop creative solutions and optimize systems for efficiency.
• Managing and optimizing data warehousing solutions for efficient data storage and retrieval, performance and scalability.
• Design, build and maintain batch or real-time data pipelines
• Advanced skills and experience with relational databases and database design
• Ability to write clean, efficient, and well-documented code.

• Bachelor’s degree in computer science, Engineering, Information Systems, or related field.
• Proficiency in languages like Python, Java, Scala, R, with experience in building and optimizing code for data processing.
• Experience working with cloud Data Warehouse solutions such as Snowflake, Redshift, BigQuery, Azure
• Hands On and strong experience in Coalesce or DBT
• Strong proficiency in scripting languages like Bash
• Strong proficiency in data pipeline and workflow management tools like Airflow, Azkaban
• Strong experience in big data technologies such as Hadoop, Spark, Kafka, Cassandra, and cloud-based solutions AWS EMR, Azure HDInsight, Google Cloud Dataproc
• Deep understanding of data modeling techniques, data warehousing principles, and experience with tools like Snowflake, Redshift, BigQuery.
• Experience with cloud platforms (AWS, Azure, GCP) and their related services.
• Proficiency in SQL and strong knowledge of various database technologies
• Expertise in designing and implementing efficient ETL and ELT pipelines
• Experience in data visualization tools like Tableau and Power BI
• Strong experience with data modelling techniques
• Strong analytical and problem-solving skills
• Provide guidance and mentorship to data engineers, leading projects and initiatives
• Keeping abreast of the latest trends and technologies in big data engineering and continuously learning and adopting new tools and techniques

• Experience with software engineering practices including CI/CD, Automated testing and Performance Engineering.
• Experience working with distributed version control and source code management tools such as Git.
• Experience in bringing initiatives and innovations that help simplify processes and automate monotonous tasks.
• Flexibility in multitasking and able to contribute beyond squad/team.
• Able to bring initiatives and innovations that help simplify processes and automate monotonous tasks.
• Experience working with Connect-Direct and Ctrl-m Scheduler, Elastic Search (ELK Stack), Splunk

1. Excellent customer-facing skills
2. Excellent written and verbal communication skills
3. Strong attention to detail and outstanding analytical and problem-solving skills.

• Income Protection Insurance
• Paid Parental and Volunteer leaves
• Employee Assistance Program (EAP)
• Flexible working arrangements (hybrid, reviewed case-by-case basis)
• Health Insurance Discount and Well-being Program
• Access to Fitness and Gym Memberships
• Salary packaging and novated leasing