About the Company:
Industrious is the largest premium workplace-as-a-service provider and home to the highest-rated workplaces in the industry. Everything we do comes down to creating great days for teams of all sizes and stages, including our own. We believe that what makes a great day at work is the people on your team and the problems you get to solve together. We’re looking for people who love thinking outside the box and thrive in a truly collaborative setting. As teammates, we encourage new ideas and toast every win. We’re excited about having a meaningful impact on people’s workplace experience.
Great days also start when everyone can be their authentic self at work. Diversity of backgrounds, thoughts, and ideas is critical to our success in delivering great workplace experiences, both for our members and for each other. Industrious is committed to creating an inclusive, respectful environment that embraces your individuality and quirkiness. You are valued for who YOU are. We celebrate our people as individuals who can accomplish great things when we work together as one team.
We are proud to have been recognized as one of America’s 500 fastest-growing companies in 2020 by Inc. Magazine and one of Forbes’ Best Startup Employers.
To learn more, visit www.industriousoffice.com/careers.
About this role:
As a Senior Data Engineer, you will play a pivotal role in enhancing our data infrastructure, optimizing data pipelines, and ensuring reliable and efficient data delivery for our organization. You will collaborate with cross-functional teams, including software engineers, business analysts, and product managers, to design, develop, and implement scalable and robust data solutions. Your expertise in data engineering and analytics will enable us to derive valuable insights from complex datasets, ultimately driving data-informed decision-making throughout the organization.
Responsibilities:
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Design and Develop Data Solutions: Architect, build, and deploy scalable and maintainable data solutions, including data pipelines, APIs, scheduled jobs, workers, etc…
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Data Modeling and Optimization: Design and implement efficient data models, ensuring data integrity, performance, and scalability. Optimize data storage and retrieval processes to improve overall system performance.
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Data Quality Assurance: Implement data quality checks, validations, and cleansing processes to ensure data accuracy, consistency, and reliability throughout the analytics systems.
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Collaboration and Documentation: Collaborate with cross-functional teams, including software engineers, business analysts, product managers, to understand their data requirements and provide technical guidance. Document data engineering processes, workflows, and best practices.
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Monitoring and Maintenance: Monitor data pipelines, proactively identify and resolve issues, and ensure high availability and performance of the data analytics systems. Implement proper data backup and recovery strategies.
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Security and Compliance: Implement data security and privacy measures, adhering to industry standards and regulatory requirements such as GDPR or CCPA.
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Continuous Improvement: Stay up to date with the latest trends and advancements in data engineering and analytics. Propose and implement enhancements and optimizations to improve the overall efficiency and effectiveness of our data infrastructure.
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Support Consumers of Data: Listen carefully to what users want out of data and support their needs. Import new data sources when necessary, and mentor stakeholders into how to consume their relevant data in our reporting tool.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
- Proven experience as a Data Engineer. At least 5 years of experience in a previous role.
- Master of a programming language, such as Python. Preference for Typescript on Node.js.
- Experience with data pipeline tools and frameworks (AirFlow, DBT, Kafka, Stitch, …).
- In-depth knowledge of relational databases. Preference for PostgresQL and AWS Redshift.
- Familiarity with cloud-based data storage and processing platforms (e.g., AWS).
- Familiarity with business intelligence reporting tools (Tableau, QuickSight, Looker, …)
- Proficiency in version control systems (e.g., Git) and agile development methodologies.
- Solid understanding of data governance, security, and compliance practices.
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Excellent communication skills, both verbal and written.
- Attention to detail and a commitment to delivering high-quality work.
