Analytics Engineer
Responsibilities
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Design, build, and maintain scalable data pipelines (ETL/ELT) that ingest, clean, transform, and load data from multiple sources into the data warehouse/lake.
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Develop and maintain data models, schemas, and transformations (e.g., with dbt) that produce reliable, well-documented, analytics-ready datasets.
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Ensure data quality, integrity, and governance: implement validation, testing, monitoring, alerting, and documentation across the data platform.
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Optimize storage, query performance, and pipeline cost/efficiency, and troubleshoot failures with robust error handling and retries.
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Partner with data analysts, data scientists, and business stakeholders to understand their needs and deliver the datasets and infrastructure they require.
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Apply security and compliance best practices to data handling (access controls, encryption, PII protection), coordinating with Security/IT as needed.
Requeriments
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Software / tools: Strong SQL and proficiency in Python for data engineering; hands-on experience with ETL/ELT and orchestration tools (e.g., Airflow, dbt), cloud data warehouses (BigQuery, Snowflake, or Redshift), and a major cloud (GCP/AWS/Azure). Version control (Git).
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Specific knowledge: Data modeling and warehousing (dimensional modeling, star schemas), batch and streaming patterns, data quality and governance, and performance optimization. Experience in fintech or high-volume transactional environments is valued.
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Expected results: Reliable, well-documented, high-quality data pipelines and datasets with strong uptime; timely, accurate data available to downstream teams; and efficient, cost-effective data infrastructure.
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Skills: Strong analytical and problem-solving skills, attention to detail, ownership and reliability, clear communication, and collaboration across technical and business teams.
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Desirable (not essential): Experience with streaming (Kafka / Pub/Sub), infrastructure-as-code, data catalog/observability tools, and system integrations; intermediate/advanced English (Portuguese a plus); and prior experience in a similar Data Engineer role.
Benefits
- 100% Company-funded Health for employees and immediate family members
- Life Insurance
- Indefinite-term contract
- 20 days of vacations, unlimited sick leave
- $2,000 USD annual Co-working Travel perk
- $2,000 USD annual Professional Development perk
- Phone finance, headphone benefit, home office equipment allowance and wellness perks
- Catered lunches
Skills
As published by lever · 11 questions · 2 written answers
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn (optional) URL, GitHub (optional) URL, Other website
Short answers (2)
- If you selected "No", please enter your preferred name. (If you selected "Yes", you may leave this field blank) optional
- What is your salary gross expectation (in the local currency and monthly/year amount). Please, consider the other benefits mentioned too.
Pick from a list (7)
- Is your preferred name the same as your legal name? optional
- This role is expected to be on site Monday, Wednesday and Thursday. Are you able to commit to that schedule? optional
- Please list your current location optional
- If you are not located in the city where this role is based, are you able to relocate? optional
- Please assess your English proficiency. optional
- How would you self-rank your SQL ability? optional
- How do you consider your Python skills? optional
Written answers (2)
- What tools for data visualization are you comfortable with?
- Do you have any family or personal connection with current or former employees at PayJoy? If yes please specify the name and relationship.