Job Title:
Senior Data Engineer (ETL, dbt, Airflow, AWS)
Location:
Toronto, ON or Remote (US)
Company:
Leni
About Us
We’re a fast-growing proptech startup building a modern AI data platform for the
multi-family real estate
industry. Our mission is to turn performance and market data into reliable, timely, decision-ready insights for operators, owners, and asset managers.
Role Overview
We’re hiring a Data Engineer to design, build, and
validate ETL pipelines
from multiple data sources - primarily
property management systems (PMS)
and improve the
stability, reliability, and scalability
of our data infrastructure as we grow. You’ll work closely with Data and Product to standardize ingestion, enforce data quality, and ship trustworthy datasets for analytics and downstream apps.
What You’ll Do
Design \& Build Pipelines:
Create robust ingestion and transformation pipelines using
Airflow
and
dbt-core
on
AWS
(S3, Iceberg, Redshift).
Source Integration (PMS):
Connect to and normalize data from PMS platforms (APIs, webhooks, SFTP, files); help to facilitate mapping schemas and validate data access reliability and integrity
Data Modeling:
Implement scalable
ETL
models and dimensional/semantic layers with
dbt
(staging, marts), including tests, documentation, and lineage.
Data Quality \& Validation:
Establish automated data checks, anomaly detection, and reconciliation against source totals; build backfill/retry strategies.
Reliability \& Observability:
Improve SLAs/SLOs with monitoring, alerting, and logging; reduce pipeline failures and mean time to recovery.
Performance \& Cost:
Tune queries and storage formats/partitioning; optimize compute and scheduling to balance performance, cost, and freshness.
Security \& Governance:
Help implement least-privilege access, secrets management, contribute to in-place SOC2 practices.
Collaboration:
Partner with BI developers to ensure datasets are analytics-ready and support Tableau performance
Qualifications
Must-Have
3–5 years
in data engineering or analytics engineering roles.
Strong
SQL
(window functions, CTEs, performance tuning) and
dbt
(models, tests, macros, snapshots).
Production experience with
Airflow
(DAG design, dependency management, retries, SLAs).
Hands-on with
AWS
data services (S3, IAM, EC2/ECS/Lambda, Iceberg/Athena/Redshift, Step Functions) and CI/CD (GitHub/GitLab actions).
Proven track record building reliable ETL/ELT pipelines from heterogeneous sources (APIs, SFTP, flat files).
Solid data quality mindset: testing, validation, lineage, and documentation.
Big Plus
Experience mining data from
PMS systems
(e.g., Yardi, RealPage, AppFolio, Entrata, ResMan) and understanding of multifamily data domains (rent roll, GL, unit/lease, delinquency, maintenance, traffic).
Python for data tooling (requests, pandas/pyarrow, boto3)
Observability/alerting tools, and workflow best practices (data contracts, CDC, incremental strategies).
Familiarity with semantic layer needs (Cube).
Our Stack (typical)
AWS, Airflow, dbt, Python, SQL, Git-based CI/CD, JS TypeScript, Tableau.
Why Join
Impact:
Your pipelines and models will be the backbone of how multifamily operators make daily decisions.
Growth:
Broad scope across ingestion, modeling, reliability, and governance in a high-ownership environment.
Team:
Collaborative, pragmatic, and product-minded data culture.
Process
·
Intro with HR / Screening
·
Hiring Manager Interview
·
Take-home assignment
·
Interview with CEO
·
Offer
Comp Range
·
190-220K + Bonus, Equity