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Data Engineer

SafetyCulture is a customer and product-led SAAS company, our mission is to help working teams get better every day, our technology platform and products give front line workers a voice and leaders the visibility to make smart decisions when driving safety, quality and continuous improvement.


As part of the Data & Analytics team, you’ll use your skills to help us understand what’s working for our customers, what’s not, and what we need to do next to improve our products and grow our business. Working as a Data Engineer, you will provide reliable, accurate & quality data sets to the Analytics team, as well as design architectures that can deliver the data on time for the analytics engineers and data analysts to use and provide value to the business with our Petabyte size data lake. SafetyCulture is expanding rapidly which requires the Data Engineer to integrate different systems and datasets from differing business contexts.


A Data Engineer at SafetyCulture is responsible for empowering the Data Analytics team with the right data model for their needs, enabling them to find insights that can make a change to SafetyCulture as a company. This is a key role in keeping the organization's knowledge organized, easily accessible, and accurate.

As a Data Engineer you collaborate with different stakeholders across the business (Finance/Marketing/Sales) to turn billions of rows of source data into highly valuable datasets and data products. SafetyCulture is expanding rapidly which requires the Data Engineer to integrate different systems and datasets from differing business contexts.


What you will be doing:
  • Deliver big data datasets on time and with quality using the most out of our infrastructure.
  • Support the design of new feature data tracking to match our patterns.
  • Apply software engineering principles to our data pipeline, providing reusable and efficient code in Python, Scala and SQL.
  • Support our infrastructure in AWS and Databricks using Terraform.
  • Manage our data architecture via orchestration tools like Airflow.
  • Manage and optimise data at scale with Data Lake (Delta), Data Warehouse (Redshift and Databricks), ML architecture and external tools (Fivetran and Segment)
  • Work closely with the Software Engineers to design efficient data contracts, ensuring the requirements of data analysts, and support the analytics engineer team with sourcing very reliable datasets.
  • Contribute to fostering an open, positive atmosphere within the team, promoting collaboration, learning, and growth.


What you will need to be successful?
  •  Experience with data engineering architecture and cloud base solutions for big data.
  • Python or Scala - Confort of writing solutions for scalable pipelines in Apache Spark.
  • Data Orchestration tools such as Apache Airflow.
  • AWS Infrastructure Experience (Terraform, EMR, S3, Glue).
  • Data warehouse experience (Redshift, Databricks or Snowflake).
  • Curiosity and self-drive to continuously learn new techniques and tools to extract value from data.
  • High level of comfort with ambiguity and ability to work in a fast-paced, agile environment in which you rapidly adapt and learn for any given business problem.


Nice skills to have:
  • Familiarity with streaming platforms as Apache Kafka
  • Experience with container technologies like Kubernetes and Docker
  • Support to data transformation tools as dbt
  • Intellectual curiosity and an understanding of what drives customer outcomes and has a positive impact on the business
  • Experience with designing data solutions for SaaS industry 


More than a job, what do you get?
  • Equity with high growth potential, and a competitive salary
  • Flexible working arrangements, we encourage you to create the best work blend while working from your home and the local SafetyCulture office
  • Access to professional and personal training and development opportunities
  • Hackathons, Workshops, Lunch & Learns
  • We encourage involvement in the community, open source work, attending talks and events, and experimenting with new technologies


Office benefits at our Sydney HQ:
  • In-house Culinary Crew serving up daily breakfast, lunch and snacks.
  • Barista coffee machine, craft beer on tap, boutique wines and a range of non-alcoholic beverages.
  • Wellbeing initiatives such as subsidized fitness programs, EAP services and generous parental leave policy.
  • Quarterly celebrations and team events, including the annual Shiplt global offsite.
  • On-site gym, table tennis, board games, books library, and pet-friendly offices.


We’re committed to building inclusive teams and cultivating a sense of belonging so our people can bring their whole authentic selves to work each day. We seek to make reasonable adjustments throughout our recruitment process to create an even playing field for all candidates. Thanks to the tireless efforts of the entire SafetyCulture team we’ve built an incredible culture which has seen us recognised as a Best Place to Work in Australia, the US and the UK. 


You can find out more about life at SafetyCulture via Youtube, Twitter, Instagram and LinkedIn.


More than 28,000 organisations use our flagship products, iAuditor and EdApp, to perform checks, train staff, report issues, automate tasks and communicate fluidly. SafetyCulture powers over 600 million checks per year, approximately 50,000 lessons per day and millions of corrective actions, giving leaders visibility and workers a voice in driving safety, quality and efficiency improvements.


To all recruitment agencies, we do not accept resumes or partnership opportunities. Please do not forward resumes to SafetyCulture or any of our employees. We are not responsible for any fees associated with unsolicited resumes.


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CEO of SafetyCulture
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Luke Anear
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What You Should Know About Data Engineer, SafetyCulture

At SafetyCulture, we are on a mission to help working teams get better every day, and we are looking for a passionate Data Engineer to join our dynamic team in Sydney. As a Data Engineer, you'll play a crucial role in the Data & Analytics team, using your expertise to support our drive for safety, quality, and continuous improvement. You'll be responsible for delivering reliable and high-quality datasets, enabling our analytics engineers and data analysts to provide actionable insights. With our expansive Petabyte-sized data lake, you'll design architectures that ensure timely and accurate data delivery across various business contexts. Collaborating closely with stakeholders from Finance, Marketing, and Sales, you'll transform billions of rows of source data into valuable datasets and data products that help shape our company's decisions. To thrive in this role, you should possess experience with data engineering, cloud solutions, and programming in Python or Scala. Your knowledge of orchestration tools, AWS infrastructure, and data warehouses will be invaluable as you help us optimize our data architecture. We're all about fostering a positive and collaborative environment, where your curiosity and self-drive for continuous learning will be welcomed and rewarded. Plus, at SafetyCulture, we offer flexible working arrangements, professional development opportunities, and a great office culture, complete with a Culinary Crew and well-being initiatives. Join us, and be a part of a company that's recognized as a Best Place to Work in Australia, the US, and the UK.

Frequently Asked Questions (FAQs) for Data Engineer Role at SafetyCulture
What are the primary responsibilities of a Data Engineer at SafetyCulture?

As a Data Engineer at SafetyCulture, you'll be responsible for delivering high-quality big data sets on time, designing new feature data tracking, applying software engineering principles to the data pipeline, and managing data architecture using tools like Airflow and AWS. Your role will involve collaborating with different stakeholders to transform large volumes of source data into highly valuable datasets that support our analytics efforts.

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What qualifications are necessary for the Data Engineer position at SafetyCulture?

Candidates applying for the Data Engineer position at SafetyCulture should have experience in data engineering architecture, cloud-based solutions for big data, and proficiency in programming languages such as Python or Scala. Familiarity with data orchestration tools like Apache Airflow and cloud platforms like AWS is also essential. Additionally, possessing a strong desire to learn and stay updated with new tools will contribute to your success.

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How does a Data Engineer at SafetyCulture ensure data quality?

A Data Engineer at SafetyCulture ensures data quality by delivering reliable and accurate datasets that support the Analytics team. This involves applying stringent data validation techniques, creating efficient data contracts in collaboration with software engineers, and optimizing data flows to maintain high data integrity. By leveraging tools like Databricks and maintaining a keen eye on data tracking features, you will actively contribute to data quality management.

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What technologies does the Data Engineer role at SafetyCulture work with?

In the Data Engineer role at SafetyCulture, you'll work with a variety of cutting-edge technologies, including AWS for cloud infrastructure, Databricks for data processing, and Apache Spark for scalable pipeline solutions. You'll also utilize orchestration tools like Airflow, database solutions such as Redshift, and leverage modern data transformation tools like Fivetran and Segment to enhance our data ecosystem.

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What growth opportunities are available for Data Engineers at SafetyCulture?

SafetyCulture is committed to the professional growth of its employees, including Data Engineers. You will have access to various training programs, workshops, and development opportunities tailored to enhance your skills. Additionally, opportunities for participation in hackathons, community involvement, and exposure to new technologies are encouraged, providing a platform for continuous learning and career advancement.

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Common Interview Questions for Data Engineer
Can you describe your experience with cloud-based data engineering solutions?

When answering this question, focus on specific cloud platforms you've worked with, such as AWS, and highlight projects where you've implemented data pipelines or managed cloud infrastructure. Provide examples of how you optimized performance or solved challenges in these environments to showcase your hands-on experience.

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How do you approach designing data architectures?

Discuss your methodology for designing scalable and efficient data architectures. Mention considerations such as data accessibility, security, and integration of different systems. Provide examples from past projects where your design choices resulted in improved data flow or insights.

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What programming languages are you comfortable with for data engineering tasks?

Identify the programming languages you have experience with, such as Python, Scala, or SQL. Share situations where you've used these languages to develop data pipelines or perform data transformations. Highlight your ability to write clean and efficient code tailored for scalability.

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How do you ensure that data is delivered on time and with quality?

Explain your strategies for maintaining timelines and data quality. Discuss your use of orchestration tools like Airflow for workflow management and any best practices you follow to conduct data validation and testing before deployment to the analytics teams.

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Can you explain a challenging data engineering problem you've encountered?

Prepare an example of a complex data engineering issue you've faced, detailing the problem, your thought process in diagnosing it, and the solutions you implemented. Highlight what you learned from the situation and how it improved your approach to similar challenges in the future.

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What is your experience with data lake and data warehouse solutions?

Elaborate on your experience with data lake technologies like Delta Lake or data warehouse platforms such as Redshift and Databricks. Share specific projects where you've utilized these solutions, describing how they helped manage large datasets and improve reporting accuracy.

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How do you collaborate with different stakeholders in your projects?

Describe your collaborative approach when working with stakeholders from various departments such as Finance, Marketing, or Sales. Highlight your communication strategies, how you gather requirements, and how you ensure their needs are met in your data engineering projects, fostering a positive working relationship.

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What tools do you use for data transformation and orchestration?

Mention the specific tools and technologies you've used, such as dbt for data transformation and Airflow for orchestration. Discuss how these tools streamline your workflow and improve collaboration with data analysts and other technical teams.

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How do you stay updated with new data engineering technologies?

Emphasize your commitment to continuous learning. Mention resources you use to stay updated, such as online courses, blogs, or attending workshops and conferences. Share how you apply new knowledge to your work to enhance your data engineering capabilities.

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What interests you about the Data Engineer position at SafetyCulture?

Articulate your interest by connecting your skills and experience with SafetyCulture’s mission and culture. Discuss what excites you about contributing to a data-driven organization and how you see yourself helping improve safety and quality through effective data engineering.

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We are helping to turn some of the greatest organisations and events into better places to work. In fact, SafetyCulture technology is used by organisations ranging from the Australian Open to NASA and the United Nations. We know that our products ...

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Full-time, hybrid
DATE POSTED
January 7, 2025

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