Data Engineer

Loopio; Canada; Remote; CAD 95.000 - 135.000; Vollzeit

Benefits dieser Stelle

Health benefits

Parental leave

Stock options

Mastery budget

Annual company retreat

Generous paid time off

Remote work subsidies

Team socials

Zusammenfassung

Loopio is seeking an experienced Data Engineer to build and support data pipelines for analytics across internal teams and Loopio's platform. You will integrate diverse data sources, including clickstream and relational data, into the Datalake and feature store to empower data-driven decision making.

You will collaborate with ML engineers, data scientists, and product managers to scale data platforms, improve reliability, and deliver insights that inform RevOps, Marketing, and CX initiatives.

Qualifikationen

• 3+ years of data engineering experience in a production environment.
• Experience with ETL and data warehousing; familiar with Inmon, Kimball, Data Vault modeling.
• Strong Python (or other language) for data manipulation.
• Hands-on with AWS services (RDS, S3, Redshift, Glue).
• Experience with Clickstream data (Amplitude, Pendo) and BI/visualization tools.
• Ability to work in a fast-growing agile software environment.

Aufgaben

• Build and maintain data pipelines, data lakes, and a data warehouse (Redshift).
• Develop Databricks-based data processing and orchestrate with Airflow or similar tools.
• Partner with data scientists and product teams to enable data-driven decisions.
• Implement scalable data automation, monitoring, and data quality checks.

Kenntnisse

SQL

Python

Data modeling

Cloud computing

Mentorship

Tools

Databricks

AWS

Redshift

Airflow

Kubernetes

Jobbeschreibung

• 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
• Developing and maintaining 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 infrastructureExperience working with data visualization and BI platforms (Quicksight, Tableau, Sisense, etc)Strong communication, collaboration, and analytical skillsExperience with ETL & Data warehousing, building Inmon/Kimball/Data Vault modelsExperience in either Python (preferrably), or other common programming language (Scala, Java) for data manipulation purposesStrong understanding of relational databases (RDS/Aurora) and NoSQL engines (Redis/DynamoDB/Neptune/etc)Experience building and supporting large-scale systems in a production environmentStrong understanding of database concepts, modeling, SQL, query optimizationHands-on experience with the AWS services (RDS, S3, Redshift, Glue, Quicksight, Athena, ECS)Ability to learn fast and translate data into actionable business resultsExperience working with Clickstream data (Amplitude, Pendo, etc)3+ years experience in a data engineering or a similar roleExperience in a high growth agile software development environmentExperience with MPP frameworks such as Spark / FlinkAbility to clearly communicate technical roadmap, challenges, and mitigationDemonstrated 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 groupsWe 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 tableExperience with container orchestration (leveraging tools like Docker, ECS, Kubernetes)Experience working with BI PaaS / SaaS solutionsExperience with Natural Language Processing techniquesExperience with graph-like data and corresponding data engines (Neo4J, Neptune, GraphFrames)Experience in AI-augmented SDLC