Data Engineer

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. Our perfect candidate has deep technical skills and is comfortable working in an evolving technology infrastructure. 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.

What You’ll Be Doing

• 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 and 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 Delta Lake).

• Orchestrate pipelines using workflow frameworks/tooling.

What You’ll Bring to the Team

• Strong understanding of database concepts, modeling, SQL, query optimization.

• Ability to learn fast and translate data into actionable business results.

• Experience in either Python (preferably), or other common programming language (Scala, Java) for data manipulation purposes.

• Hands-on experience with AWS services (RDS, S3, Redshift, Glue, QuickSight, Athena, ECS).

• Strong understanding of relational databases (RDS/Aurora) and NoSQL engines (Redis/DynamoDB/Neptune/etc).

• Experience with ETL & Data warehousing, building Inmon/Kimball/Data Vault models.

• Experience with MPP frameworks such as Spark / Flink.

• Experience with CI/CD tools (Jenkins) and pipeline orchestration tools (Databricks Jobs, Airflow).

• Experience working with data visualization and BI platforms (QuickSight, Tableau, Sisense, etc).

• Experience working with clickstream data (Amplitude, Pendo, etc).

• Experience in a high-growth agile software development environment.

• Experience building and supporting large-scale systems in a production environment.

• Strong communication, collaboration, and analytical skills.

• Demonstrated ability to work with a high degree of ambiguity, and leadership within a team (mentorship, ownership, innovation).

• 3+ years experience in a data engineering or similar role.

• Ability to clearly communicate technical roadmap, challenges, and mitigation.

Bonus Qualifications

• Experience with container orchestration (leveraging tools like Docker, ECS, Kubernetes).

• Experience working with BI PaaS / SaaS solutions.

• Experience with Natural Language Processing techniques.

• Experience in AI-augmented SDLC.

• Experience with graph-like data and corresponding data engines (Neo4J, Neptune, GraphFrames).