Data Engineer (Intermediate)

Company

Punt is a Vancouver-based, founder-led technology company behind two of the largest social casinos in North America. We're evolving into a super app that brings social gaming and exciting new verticals together in one experience. Our backend already handles high-volume, real-money transactions at scale. We're building toward a new category: the most advanced and engaging social gaming platform in the world.

Role Overview

We are looking for a Data Engineer to join our Data Spine function — the team that owns the canonical event contract, the warehouse, and the serving layer that every other data function depends on. Your primary focus is ingestion: making sure raw events from the product, third-party providers, and operational systems land reliably, freshly, and with the right contracts in place.

You will build and maintain the pipelines that turn raw events into trustworthy, well-governed data across a medallion architecture (bronze → silver → gold). Your work underpins everything downstream — BI/Analytics depends on you for clean numbers, and Applied AI depends on you for features and training data.

This role is ideal for an engineer who cares deeply about data quality, pipeline reliability, and building infrastructure that other teams can trust without thinking about it.

Responsibilities

• Design, build, and maintain scalable data ingestion pipelines that process high-volume event streams from the product, third-party game providers, payment systems, and operational sources.

• Own the bronze layer of the medallion architecture — landing raw events reliably with schema validation, contract enforcement, and lineage tracking.

• Build and evolve transformation pipelines across the medallion layers, ensuring data is clean, deduplicated, and conforms to the canonical data model.

• Implement and maintain data quality checks, alerting, and observability across the ingestion and transformation pipeline.

• Support PII masking, data governance, and compliance requirements (e.g. HMAC-SHA256 masking before data reaches the warehouse).

• Collaborate with the Lakehouse Platform Engineer on warehouse architecture, serving layer design, and platform reliability.

• Maintain and improve pipeline orchestration, scheduling, worker health monitoring, and incident response.

• Ensure canonical alignment across provider data — one version of reality for metrics like GGR, NSGR, and player activity.

• Participate in on-call rotations for data pipeline availability and freshness.

• Document data contracts, pipeline architecture, and operational runbooks.

Required Qualifications & Experience

• 5+ years of professional data engineering experience, with ownership of production ingestion and transformation pipelines.

• Strong hands-on experience with Python for data engineering (pipeline code, scripting, tooling).

• Production experience with a modern data warehouse such as Redshift, BigQuery, Snowflake, or Databricks.

• Experience with pipeline orchestration tools such as Prefect, Airflow, Dagster, or equivalent.

• Solid understanding of medallion architecture (bronze/silver/gold) or equivalent layered data modeling patterns.

• Experience with streaming and batch ingestion patterns (Kafka, Kinesis, CDC, file-based, API-based).

• Strong SQL skills and experience building transformation logic for analytical workloads.

• Understanding of data quality frameworks, schema enforcement, contract testing, and data validation.

• Experience with cloud infrastructure (AWS preferred — EC2, S3, IAM, VPC, CloudWatch).

• Familiarity with version control (Git), CI/CD for data pipelines, and infrastructure-as-code concepts.

• Strong communication skills and ability to work cross-functionally with analytics, AI, and engineering teams.

Preferred Skills & Nice-to-Haves

• Experience in gaming, social casino, fintech, or high-volume transactional data environments.

• Experience with PII masking, data governance, and compliance in regulated or audit-sensitive environments.

• Familiarity with dbt for transformation layer management.

• Experience with data cataloging, metadata management, or data lineage tools.

• Exposure to real-time data serving or low-latency feature stores.

• Experience building canonical data models across multiple upstream providers or systems.

• Familiarity with cost optimization for cloud data infrastructure.

Why Join Us?

• Own the ingestion backbone of a fast-growing gaming platform — your work is the foundation everything else is built on.

• Work inside a clearly defined Data Spine function where reliability, quality, and governance are the priorities — not context-switching across analytics and modeling.

• Help build the data platform from its current state into a scalable, well-governed lakehouse architecture.

• Collaborate closely with BI/Analytics and Applied AI teams who depend on your work — high visibility and high impact.

• Competitive compensation and comprehensive benefits.