At a Glance
- Tasks: Build and support data pipelines for analytics, empowering teams with data-driven insights.
- Company: Join Loopio's innovative Data Engineering Team transforming RFP responses.
- Benefits: Robust health benefits, remote work subsidies, generous PTO, and employee stock options.
- Other info: Dynamic team culture with opportunities for mentorship and professional growth.
- Why this job: Make a real impact by streamlining data processes and driving business decisions.
- Qualifications: 3+ years in data engineering, strong skills in Python, SQL, and cloud technologies.
The predicted salary is between 90000 - 110000 $ per year.
Loopio’s Data Engineering Team works together on a mission to transform the RFP response process into a rapid and seamless experience. Our team works across all platform portfolio features and delivers innovative solutions where it matters the most for our customers.
We are looking for an experienced Data Engineer to build and support the delivery of data pipelines, used for analytics both internally by Loopio’s teams, embedded within the Loopio platform for our customers. This is a unique opportunity to join a growing team of creative and passionate individuals committed to solving real world problems. You will empower engineers, product, and data scientists with tools that enable and streamline data-driven decision making, analysis, and feature development.
You will partner closely with ML Engineers, Architects and Data Scientists, Product Managers, and other business stakeholders to help us take Loopio’s data value to the next level. Be responsible for building, evolving and scaling data platforms and ETL pipelines, with an eye towards growth of our business and reliability of our data.
Promote data-driven decision making across the organization through data expertise. Build advanced automation tooling for data orchestration, evaluation, testing, monitoring, administration, and data operations. Integrate various data sources into our Datalake, including clickstream, relational, and unstructured data. Develop and maintain a feature store for use in analytics & modeling.
Partner with data scientists to create predictive models to help drive insights and decisions, both in Loopio’s product and internal teams (RevOps, Marketing, CX). Work closely with stakeholders within and across teams to understand the data needs of the business and produce processes that enable a better product and support data-driven decision-making.
Build scalable data pipelines using Databricks, and AWS (Redshift, S3, RDS), and other cloud technologies. Build and support Loopio’s data warehouse (Redshift) and data lake (Databricks deltalake). Orchestrate pipelines using workflow frameworks / tooling.
Benefits:
- Robust Health Benefits
- Extended Parental Leave
- Employee Stock Options
- Professional Mastery Budget
- Annual Company Retreat
- Generous Paid Time Off Program
- Remote Work Subsidies
- Team Socials
Our perfect candidate has deep technical skills and is comfortable working in an evolving technology infrastructure. Experience working with data visualization and BI platforms (Quicksight, Tableau, Sisense, etc). Strong communication, collaboration, and analytical skills. Experience with ETL & Data warehousing, building Inmon/Kimball/Data Vault models. Experience in either Python (preferably), or other common programming language (Scala, Java) for data manipulation purposes.
Strong understanding of relational databases (RDS/Aurora) and NoSQL engines (Redis/DynamoDB/Neptune/etc). Experience building and supporting large-scale systems in a production environment. Strong understanding of database concepts, modeling, SQL, query optimization. Hands-on experience with the AWS services (RDS, S3, Redshift, Glue, Quicksight, Athena, ECS).
Ability to learn fast and translate data into actionable business results. Experience working with Clickstream data (Amplitude, Pendo, etc). 3+ years experience in a data engineering or a similar role. Experience in a high growth agile software development environment. Experience with MPP frameworks such as Spark / Flink.
Ability to clearly communicate technical roadmap, challenges, and mitigation. Demonstrated ability to work with a high degree of ambiguity, and leadership within a team (mentorship, ownership, innovation). Experience with CI/CD tools (Jenkins) and pipeline orchestration tools (Databricks Jobs, Airflow).
We recognize that all too often, potential candidates don’t apply for a position simply because they don’t hit every single criteria included in the job description—particularly members of underrepresented groups. We understand that a resume can only showcase so much during the applicant stage, so we’ve created prompts in the application for you to share more about yourself. If you’ve made a career transition (or a few!), you’re self taught in a new role, or you have skills/experience you’d like to highlight, we want to hear more about what you could bring to the table.
Experience with container orchestration (leveraging tools like Docker, ECS, Kubernetes). Experience working with BI PaaS / SaaS solutions. Experience with Natural Language Processing techniques. Experience with graph-like data and corresponding data engines (Neo4J, Neptune, GraphFrames). Experience in AI-augmented SDLC.
Data Engineer employer: Loopio
At Loopio, we pride ourselves on being a remote-first employer that champions flexibility and collaboration across global teams. Our supportive culture fosters continuous learning and innovation, offering employees opportunities for professional growth through regular feedback, dedicated mastery allowances, and a range of health and wellness benefits. With co-working options in vibrant locations like Downtown Toronto and Vancouver, Loopers can thrive in an environment that values creativity and connection while making a significant impact on our marketing website and overall web experience.
