Sr. Data Engineer

Team: Data & Analytics

Location: Atlanta, GA

Commitment: Full-time

Workplace Type: remote

Salary:

Heres What Youll Be Doing Day-to-Day:

PR-driven shipping: Opening and merging pull requests for new or updated Dagster jobs, assets, schedules, and sensors, plus dbt models, tests, and documentation.
Infrastructure tweaks: Writing occasional Terraform for secrets, environment variables, or job sizing when a pipeline needs it.
Pipeline implementation: Building and debugging Python pipelines covering REST/API syncs, large Postgres extracts, Parquet loads, and Snowflake COPY operations.
Airbyte management: Configuring or troubleshooting Airbyte connections wherever managed sync is the right fit.
Production monitoring: Watching production runs and investigating failures related to IAM, OOM, Spot instances, or bad watermarks.
Backfills & catch-ups: Running backfills and incremental catch-ups with a clear story for what landed and why.
Modeling partnership: Working with analytics and product on dim/fct/x_fct design, incremental strategies, and data quality.
Code review & runbooks: Participating in code review, release prep, and writing short runbooks so others can operate your pipelines when youre out.

Heres What Youll Need to Be Successful:

Warehouse fundamentals: Solid grasp of relational databases and warehouse patterns — keys, grain, normalization vs. star schema, and how SCD behavior gets encoded.
Orchestration experience: Practical, hands-on Dagster (or Airflow) experience — not just writing SQL inside a scheduler UI.
dbt proficiency: Real experience building and maintaining models, tests, and documentation in dbt.
Python at scale: Comfort reading and writing Python that moves data at scale across extract, transform, and load steps.
AWS working knowledge: Practical familiarity with S3, IAM, and ECS/Fargate at a debug my job level.
EL tool familiarity: Experience with Airbyte or similar extract-and-load tools.
PR discipline: The discipline to write pull requests others can easily review, and to give equally rigorous reviews in return.
Reliability mindset: A track record of keeping pipelines healthy and modeling consistent across full refresh and incremental paths, without becoming a single point of failure.

The Interview Process:

• Your application will be reviewed for possible next steps by a real human being from the PeopleOps team.
• If you meet eligibility requirements, the next step would be a video interview with a member of the PeopleOps team for about thirty (30) minutes.
• If warranted, the next step would be a video interview with our Principal Data Scientist for forty-five (45) minutes.
• If warranted, the next step would be a video panel interview with key stakeholders at PadSplit for one and a half (1.5) hours.
• If warranted, the next and final step would be a video interview with a key leader in the company for thirty (30) minutes.
• If warranted, we move to offer!

Compensation, Benefits, and Perks:

Fully remote position - we swear!
Competitive compensation package including an equity incentive plan and company-wide bonus opportunity
National medical, dental, and vision healthcare plans
Company provided life insurance policy
Optional accidental insurances, FSA, and DCFSA benefits
Unlimited paid-time (PTO) policy with eleven (11) company-observed holidays
401(k) plan 
Twelve (12) weeks of paid time off for both birth and non-birth parents
The opportunity to do what you love at a company that is at the forefront of solving the affordable housing crisis

Please note: Although the job posting says its in Atlanta, Georgia, this is a fully remote position. This is a result of our Applicant Tracking System requiring a location to post the role on LinkedIn.