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Job Description & Scorecard Generator

Pick a role and get two documents in seconds: the job description you publish, and the hiring scorecard your interviewers use, with weighted competencies and what each interview round evaluates.

01
Job description
Responsibilities, must-haves and logistics, ready to post.
Public
02
Hiring scorecard
Outcomes, weighted competencies and scoring anchors.
Internal
03
What it costs
Monthly cost by country, next to the US salary.
2026 data
Area
Role
Level
Mid
Senior
Lead
What will this person do? Optional
The more specific, the better the brief.
0 / 3,000
Team time zone Optional
Start date Optional
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Takes about 15 seconds
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Your hiring brief

Senior Data Engineer

Senior
2 interview rounds
Generated in 11 seconds

Senior Data Engineer

As a Senior Data Engineer, you will own end-to-end responsibility for our data pipelines across Airflow, dbt, and Snowflake, and lead the migration of batch processing to Kafka-based streaming. You will collaborate with analytics and engineering partners to deliver reliable, scalable data products, while mentoring two mid-level engineers.

Responsibilities
01
Own and operate production data pipelines in Airflow and dbt, ensuring correctness, performance, and observability.
02
Design and implement data models in Snowflake to support analytics and downstream applications.
03
Lead the migration of existing batch jobs to Kafka streaming, including event design, processing patterns, and backfills.
Must-have
Hands-on experience operating Airflow and dbt pipelines in production.
Experience modeling and transforming data in Snowflake for analytics.
Nice-to-have
Experience with CI/CD for data engineering workflows.
Experience defining event schemas and governance for streaming systems.
What success looks like in 12 months
Reliable, monitored pipeline operations in production
High-quality data modeling in Snowflake
Successful migration from batch to Kafka streaming
Logistics
Schedule
Full-time, 40 hours a week
Location
Remote from Latin America
Hours
Overlap with US Central time zone
About the company
To complete before publishing
[About your company: what you build, your stage and team size]
Mission

Own and improve production data reliability and scalability by leading pipeline engineering in Airflow/dbt/Snowflake and enabling streaming-first processing with Kafka.

Outcomes for the first 12 months
[X]Fill in your targets
01
Reliable, monitored pipeline operations in production
Maintain data pipeline health with incident volume at or below [X] per quarter and reduce mean time to recovery to [Y] hours or less
02
High-quality data modeling in Snowflake
Increase dbt test coverage to [X] % of critical models and reduce data quality issues detected after release by [Y] % during the first 12 months
03
Successful migration from batch to Kafka streaming
Migrate [N] production workloads from batch to Kafka streaming and achieve end-to-end freshness of [X] minutes (or better) for those workloads
Competencies

Weights add up to 100. Score every candidate against the same anchors.

Pipeline ownership
Technical · Evaluated in Round 1
26%

The role requires end-to-end accountability for production pipelines in Airflow/dbt/Snowflake.

Weak · 1

Discusses components separately and cannot describe ownership from change to incident resolution.

Meets · 2

Explains how they manage deployments, validate data outputs, and respond to incidents for pipelines they own.

Strong · 3

Walks through a full lifecycle (design → implementation → testing → deployment → monitoring → incident learning) and shows how they prevent and recover from failures using concrete practices.

Kafka streaming migration
Technical · Evaluated in Round 2
22%

Moving from batch to streaming is central to the role and requires reliable processing design.

Weak · 1

Focuses on moving data without addressing reliability, ordering, or reprocessing semantics.

Meets · 2

Explains streaming design considerations (event structure, consumer behavior, backfills) and how they validate correctness.

Strong · 3

Describes robust streaming patterns (idempotency, handling late/out-of-order events, replay/backfill approach) and how they measure freshness and correctness post-migration.

Interview rounds
Round 1
Engineering Manager
60 min

Senior Data Engineering Leadership Interview

Evaluates
Pipeline ownership
26%
Snowflake modeling
18%
Mentorship and reviews
7%
Q1
Tell us about an Airflow/dbt/Snowflake pipeline you owned end to end. How did you design it, test changes before release, monitor it in production, and handle an incident?
Q2
Describe a Snowflake data modeling approach you used to support analytics consumers (grain, incremental strategy, keys/materializations). How did you validate correctness and performance, including backfills?
Round 2
Staff Data Engineer
60 min

Streaming Migration and Reliability Interview

Evaluates
Kafka streaming migration
22%
Data quality & monitoring
17%
Performance and cost optimization
10%
Q1
Walk through a migration from batch processing to Kafka streaming. How did you handle correctness during replay/backfills, idempotency, and late or out-of-order events?
Q2
Explain how you implement data quality and monitoring for streaming/batch pipelines (what you measure, how you set thresholds, and how alerts drive incident response). Include an example of reducing incidents or MTTR.
Red flags
!
Claims ownership of end-to-end pipelines but cannot describe validation, monitoring, deployment, or incident handling specifics.
!
Proposes batch-to-streaming approaches without addressing reliability semantics (replay, idempotency, ordering/late events).
!
Relies on manual validation or informal checks for production data quality rather than automated tests and monitoring.
From Teilur's 2026 salary table

What this role costs

Monthly all-in cost of a Senior Data Engineer hired through Teilur, next to the US salary for the same role. 80% goes to the talent, 20% is Teilur's fee.

United States
$17,000/mo
Argentina
$5,625 talent · $1,425 fee
$7,050/mo
Save 59%
Colombia
$6,875 talent · $1,725 fee
$8,600/mo
Save 49%
Brazil
$8,125 talent · $2,025 fee
$10,150/mo
Save 40%
Mexico
$8,125 talent · $2,025 fee
$10,150/mo
Save 40%
Bar length is the cost relative to the US salary.
Compare the four countries in detail →
Next step

Send this role to Teilur and meet a shortlist in about 5 days

We use this job description and scorecard to search our network of pre-vetted Latin American talent. Flat 20% fee, no commitment.

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We'll use the brief you just generated to start the search. We reply within one business day.

Senior Data Engineer · Senior · Within 30 days
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What you get

Choose one of 93 roles across engineering, data, product, design, marketing, sales, finance and operations, set the level and, if you want, add a few lines about the work. In about 15 seconds you get a hiring brief in three parts.

  • A job description ready to post: summary, responsibilities, must-have and nice-to-have requirements, what success looks like after a year, and the working conditions.
  • A hiring scorecard for your interviewers: the mission of the role, measurable 12-month outcomes, five to seven weighted competencies and the interview rounds that evaluate them.
  • What the role costs: the monthly all-in cost of hiring it in Argentina, Brazil, Colombia and Mexico through Teilur, next to the US salary for the same role.

Job description vs. hiring scorecard

They answer different questions. The job description is public: it tells candidates what the job is and who should apply. The scorecard is internal: it tells your interviewers what to look for, how much each thing matters and how to tell a weak answer from a strong one.

Writing them together keeps them consistent. Every must-have in the job description is a competency on the scorecard, so you never interview for something you didn't ask for, or ask for something nobody interviews.

How the scorecard works

Each competency has a weight, and the weights add up to 100, so the team agrees up front on what matters most. Each one comes with three anchors, weak, meets and strong, that describe observable behavior, so two interviewers score the same answer the same way.

Every competency is assigned to an interview round, and every round evaluates at least one competency. The generator proposes three rounds, or two if you need the person within 30 days. Numeric targets in the outcomes are left as placeholders like [X]%, because only you know your starting point.

Where the cost figures come from

The figures come from Teilur's 2026 salary table, the same one behind our Where Should I Hire tool. The AI writes the text; it never writes a number. The all-in cost is what you pay each month: 80% goes to the professional and 20% is Teilur's flat fee.

Need someone for this role? Send us the brief and meet a shortlist of pre-vetted Latin American candidates in about 5 days.

Generate your brief

Frequently asked questions

Is the generator free?

Yes. There is no sign-up and nothing to install. You only share your contact details if you want Teilur to search for candidates.

Can I edit the job description before posting it?

Yes. Copy it and adjust it in your ATS or job board. Fill in the part about your company, which is left as a placeholder on purpose: the generator never invents facts about your business.

Why doesn't the job description include a salary?

Because you set the pay. Teilur's salary table is a reference, and putting it in a public posting would commit you to it. The cost section shows it to you privately instead.

Do you store what I type?

No. Your notes are sent to our AI provider only to write the brief, and we don't save them. If you send the role to Teilur, we receive the brief and your contact details to start the search.

Which roles and levels are covered?

93 roles across seven areas, at Mid, Senior and Lead level: the same roles Teilur recruits for in Argentina, Brazil, Colombia and Mexico.