About the role: We’re looking for a hands-on Data Engineer to join us on a 12-month max-term contract and play a key role in supporting and scaling our growing data infrastructure. In this role, you’ll be responsible for building and maintaining scalable ETL/ELT pipelines using Databricks and modern cloud tools. You’ll also step in to temporarily support our business intelligence needs, developing and maintaining reports and dashboards in ThoughtSpot (or a similar BI platform). You’ll collaborate closely with our Lead Data Engineer, who will provide architectural guidance and help drive the strategic direction of our data transformation initiatives. This role is a great fit for a data engineer who enjoys working across the full data stack—from raw data ingestion and transformation all the way to the BI layer—with a strong focus on data quality, reliability, and usability. We offer a hybrid work arrangement: 3 days in the office and 2 days remote each week, giving you the flexibility to do your best work. Key Responsibilities: Data Engineering Build, maintain, and optimize robust ETL/ELT pipelines using Databricks. Contribute to the design and implementation of data lake and data warehouse architecture. Translate business requirements into reliable and scalable data solutions. Collaborate with the Lead Data Engineer on data modeling, pipeline design, and cloud infrastructure best practices. Implement monitoring, alerting, and logging for data pipelines to ensure data integrity and reliability. Participate in sprint planning, technical documentation, code reviews, and team collaboration rituals. BI & Reporting Support Maintain and support dashboards and reports in ThoughtSpot. Assist stakeholders with ad hoc data queries and visualization needs. Ensure availability and accuracy of key business metrics during the analyst’s leave period. Translate complex datasets into usable, decision-support insights. Key Requirements: Essential Strong experience building and managing ETL/ELT pipelines in Databricks or similar platforms. Proficiency in Python and SQL for data processing, transformation, and analysis. Deep knowledge of data modeling and warehousing concepts. Experience with BI tools, preferably ThoughtSpot (or Power BI, Tableau, Looker). Solid version control and collaboration practices (e.g., Git). Ability to collaborate closely with both technical and non-technical team members. Effective communication and problem-solving skills. Desirable Exposure to DevOps practices such as CI/CD (e.g., Azure DevOps), infrastructure as code (e.g., Terraform). Experience working in a remote or distributed team environment. Experience working with cloud environments (AWS, Azure, or GCP). Familiarity with AWS services like S3, Lambda, EC2, SQS, and SNS. Personal Attributes Curious, proactive, and eager to learn. Comfortable balancing engineering depth with occasional BI support. Strong ownership mindset and attention to detail. Organized and efficient; able to manage priorities across domains. If you would like to be a part of the Wilbur team then please submit your application. We look forward to hearing from you!
