- 5+ years of solid experience as a Data Engineer with Machine Learning exposure.
- Breadth of experience using different tools and techniques.
- Extensive experience in a data-related role, e.g. working with Databricks in data warehousing and analytics contexts and creating automated ETL processes.
- Streaming (Spark, Kafka or similar)
- Python and/or Scala, relevant Python ML, libraries and SQL proficiency
- Experience building robust production data pipelines using the best industry practices with experience of data preparation and resolution of data quality challenges.
- Testing and validation of Data Models and Data Pipelines.
- AWS experience across one or more of the following EC2, Kinesis, SQS, ElastiCache, Lambda and S3
- Experience with infrastructure as code including Terraform or CloudFormation
- Deep knowledge on how to structure, develop and maintain relational databases such as MySQL and showcase your experience using data modeling techniques.
- Ability to work independently and also contribute to overall architecture and design.
- "Data wrangler" mindset: embraces complexity and ambiguity, overcomes challenges and obstacles in order to deliver a working solution.
- Decision-making: able to view a problem from multiple perspectives, select the best approach, and provide a concise rationale for the choice.
- Outcome-focused: able to balance the need for a robust, elegant technical solution with the need for a market-ready solution.
- Desirable: Experience building, administering and scaling ML processing pipelines preferable in Databricks.
- Refine, design, estimate and deliver product requirements particularly data based features.
- Work with a cross-functional team in an agile methodology
- Collaborate with others to design, develop and maintain highly scalable data pipelines that power data driven products & customer facing insights.
- Working with cloud-based data storage and processing services to build scalable and cost-effective data solutions.
- Create and optimize ETL processes to move and transform data from various sources into our data systems, ensuring data consistency and integrity.
- Develop, construct, install, test and maintain data architectures (databases, large-scale processing systems, and data pipelines) that support data extraction, transformation, and loading (ETL) processes.
- Adhering to the standards and data governance practices of the organisation, e.g. ensuring data quality, privacy, security, auditability and control throughout the data lifecycle.
- Develop and maintain data models, schemas, and database designs to support business needs and reporting requirements.
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Senior Data Engineer - Sydney, Australia - SiteMinder Group
Description
At SiteMinder we believe the individual contributions of our employees are what drive our success. That's why we hire and encourage diverse teams that include and respect a variety of voices, identities, backgrounds, experiences and perspectives. Our diverse and inclusive culture enables our employees to bring their unique selves to work and be proud of doing so. It's in our differences that we will keep revolutionising the way for our customers. We are better together
What We Do...
We're people who love technology but know that hoteliers just want things to be simple. So since 2006 we've been constantly innovating our world-leading hotel commerce platform to help accommodation owners find and book more guests online - quickly and simply.
We've helped everyone from boutique hotels to big chains, enabling travellers to book igloos, cabins, castles, holiday parks, campsites, pubs, resorts, Airbnbs, and everything in between.
And today, we're the world's leading open hotel commerce platform, supporting 40,000 hotels in 150 countries - with over 100 million reservations processed by SiteMinder's technology every year.
About the Senior Data Engineer role...
A key addition to our engineering team to assist us with our transformation program. This is for an all-rounder Data Engineer who can be dynamic and play a role in different aspects of working with data, from ingestion, setting pipelines to a ML engineer who can work with models such as selecting the right model, picking features and tuning parameters.
You will be someone who knows what good looks like and has set up robust production data pipelines using Databricks and associated products.
What you have...
What you'll do...
Hybrid working model (in-office & from home)
Mental health and well-being initiatives
Generous parental (including secondary) leave policy
Paid birthday, study and volunteering leave every year
Sponsored social clubs, team events, and celebrations
Employee Resource Groups (ERG) to help you connect and get involved
Investment in your personal growth offering training for your advancement
Does this job sound like you? If yes, we'd love for you to be part of our team Please send a copy of your resume and our Talent Acquisition team will be in touch.
When you apply, please tell us the pronouns you use and any adjustments you may need during the interview process. We encourage people from underrepresented groups to apply.
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