Software Engineer, Data Platform

Lattice•Remote - Canada, ON

17h•Remote

About The Position

This is Engineering at Lattice Lattice’s Engineering team is continuously working to better both our product and our craft. We use a modern, cutting-edge tech stack and love experimenting with new technologies. We strive for maintainable, robust, and performant code. We’re highly collaborative and continuously iterative and work closely with designers and product managers. We prioritize not only great technical architecture but also an amazing product experience. As a Data Platform Engineer, you will play a pivotal role in designing and maturing Lattice’s centralized data platform — starting with a modern data lakehouse built on AWS. This is an opportunity to be a founding member of a new team, build the backbone of our data ecosystem, and directly influence the intelligence and interconnectedness of our products. You will architect and implement foundational data infrastructure that enables scalable storage, reliable data processing, and secure access across the organization. In addition to building the lakehouse itself, you will design and maintain a set of reusable connection and query utilities that empower internal stakeholders to interact with the platform efficiently and safely.

Requirements

2+ years of experience in software, data, or analytics engineering with exposure to a centralized “data platform” or large-scale data infrastructure project.
Fluency in SQL and a general purpose programming language; Python or TypeScript preferred
Familiarity with a data warehouse/lakehouse platform e.g. Snowflake, Redshift, BigQuery, Databricks
Familiarity with AWS services or their equivalents e.g. IAM, Glue, Lambda, Athena, Redshift, Kinesis, EKS

Nice To Haves

Hands-on experience with data processing frameworks like dbt, Spark, Kafka Streams, or Flink
Willingness to learn and curiosity into how trustworthy, insightful data can unlock value for our users

Responsibilities

Standardize Lattice’s data infrastructure and practices through establishing a simple, cohesive, and reliable platform that seamlessly integrates internal and partner data
Design, develop, and deploy scalable data pipelines that can ingest, process, and serve data across multiple teams for batch and streaming workloads.
Make data effortlessly accessible – abstract infrastructure complexity through reusable SDKs, libraries, and tooling
Shape data governance practices ensuring access to data is secure, compliant, and high-quality.
Partner with Engineering, Product, and business leaders to identify data needs and implement solutions that align with strategic objectives.