OMG!! NEEDED NOW!! Data Engineer – PostgreSQL, Python & Warehouse Pipelines – Fast Growing Marketing CANADIAN Company

Hey there! I'm looking for a HIGHLY TEACHABLE (Willing to Learn) mid-level Data Engineer with excellent written English to build and maintain the data pipelines and warehouse logic underneath our client dashboards.

In the beginning, this is an on-call/part-time job, but it can grow into a full-time role where you'll own more of the data layer if you prove to be a great fit.

Watch this video to learn more about how our agency works and to also see my personality and style:
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ABOUT YOU:

• Great communicator in writing
• Detail-oriented and structured
• Extremely reliable
• Positive, no-excuse attitude
• Validates your own work against live data before reporting it done
• Comfortable saying "I do not know yet" instead of guessing

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IMPORTANT – SCREENING PROCESS:

Our hiring process includes two stages:

Stage 1 – Initial Technical Screening (Unpaid)
Selected applicants may be asked to complete a short, time-bounded screening exercise (approximately 15–20 minutes). This screening is designed to assess problem-solving approach and technical reasoning only. It does not require production-ready code, live system access, or work that will be used operationally. Submissions are used solely for evaluation.

Stage 2 – Final Technical Assessment (Paid)
Candidates who advance past Stage 1 may be invited to complete a structured, time-limited technical assessment using a controlled sample dataset created specifically for evaluation purposes. Final assessment submissions must include a Loom video walkthrough explaining the candidate's approach, reasoning, and implementation decisions.

This stage:

• Is paid at a fixed rate upon written acceptance
• Requires submission of both the technical output and Loom video walkthrough
• Is clearly defined and time-bounded
• Is designed solely to evaluate technical ability
• Is not connected to live client systems or production work

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KNOWLEDGE REQUIRED:

• Strong PostgreSQL: window functions, CTEs, query plans, indexing. You should be able to explain why a query is slow and prove it from the plan
• Python for data work: requests, pandas or equivalent, and the discipline to write something that runs unattended
• Experience building pipelines that sync from third-party APIs into a warehouse, and fixing them when a vendor changes something without telling anyone
• Regex and parsing logic for messy real-world data, tested against the real data and not against what you assume it looks like
• Comfort running benchmarks and migrations against tables in the tens of millions of rows

Bonus:

• dbt, Airflow, or similar orchestration
• n8n
• Grafana or BI tools
• Experience with a CRM or ad platform API
• Healthcare data

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ABOUT ME (Alex):

• CEO with over 20 years of experience in digital marketing
• I move very fast and expect the people I work with to operate with clarity and discipline
• I reward performance and reliability
• I run the company remotely and am located in Indonesia

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ABOUT THE POSITION:

We run attribution and KPI infrastructure for clients in healthcare and automotive. Our warehouse joins ad platforms, call tracking, CRM, and practice management systems into one picture of what a marketing dollar actually produced.

This is not a dashboard job and it is not a reporting job. You will work on the pipelines underneath them. Your role will include writing and optimising warehouse SQL, building and maintaining Python sync pipelines, running benchmarks and migrations against live data, and investigating discrepancies to root cause. When two systems disagree, you find out which one is wrong and why.

Work will be assigned in clearly defined task blocks with specific deliverables and validation criteria.

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ABOUT THE COMPENSATION:

We offer DAILY PAYMENTS on a task-by-task basis through WISE, ensuring timely and efficient compensation for your work.
We pay bonuses for great work – we reward results.
13th-month bonus for candidates who qualify for a full-time position.

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HOW TO APPLY:

Send an email with the subject line: Awesome Backend Developer
Include your resume

In your email , answer this: A weekly audit compares two systems and reports a 4% match rate. The documented expected match rate is 96%. Someone has already checked that both systems have data for the period and that the join key exists on both sides. What are the first three things you check, and in what order? Tell me what would make you conclude the audit itself is wrong rather than the data.

Congratulations! You made it to the end, so what are you waiting for?
Please email me at: ----------