Hire Data Management Engineers
Leverage top Data Management Engineers from LatAm. Experts in data quality, lineage, and governance ready to join your remote team in just 21 days.
Hire Remote Data Management Engineers
Óscar is a data strategist who translates metrics into useful operational decisions.
- Data Analysis
- Analytics Strategy
- Dashboarding
- Data Storytelling
- BI Tools
Héctor is a data strategist translating trends into clear, business-focused actions.
- Business Intelligence
- SQL & Data Lakes
- ETL Tools
- Descriptive Analytics
- Data Quality Assurance
Renan is a data specialist building structured solutions to optimize operations.
- Data Reporting
- Analytics Tools
- Data Cleanup
- SQL
- Process Analysis
Carlos excels in data science, blending innovation with precision. A master at turning data into insights.
- Statistics
- Data Cleaning
- Python
- Feature Engineering
- Machine Learning
Natalia excels in data analysis, delivering insights with precision and creativity.
- Power BI
- Data Visualization
- A/B Testing
- Excel
- SQL
"Over the course of 2024, we successfully hired 9 exceptional team members through Lupa, spanning mid-level to senior roles. The quality of talent has been outstanding, and we’ve been able to achieve payroll cost savings while bringing great professionals onto our team. We're very happy with the consultation and attention they've provided us."
“We needed to scale a new team quickly - with top talent. Lupa helped us build a great process, delivered great candidates quickly, and had impeccable service”
“With Lupa, we rebuilt our entire tech team in less than a month. We’re spending half as much on talent. Ten out of ten”
Data Management Engineers Skills
Data Governance
Implement rules for data quality, access, and compliance.
Master Data Management
Maintain consistent, accurate data across systems.
Metadata Management
Track and manage data lineage and definitions.
Data Architecture
Design scalable structures for storage and retrieval.
ETL Development
Build robust pipelines to process and move data.
Access Controls
Define and enforce permissions across data systems.
Data Management Engineers Soft Skills
Precision
Maintain consistency and accuracy across data systems.
Process Orientation
Follow structured methods for governance and control.
Collaboration
Work with data teams, analysts, and infrastructure leads.
Problem Solving
Diagnose and resolve data quality and integrity issues.
Responsibility
Own systems that power business-critical decisions.
Adaptability
Respond to changing regulations and system needs.
How to Hire Data Management Engineers with Lupa
Ensure scalable, reliable infrastructure with top Data Management Engineers. Access talent via our IT Recruiting Agency in Latin America, scale with Tech Staffing Services, or embed hiring through our RPO solutions.
Together, we'll create a precise hiring plan, defining your ideal candidate profile, team needs, compensation and cultural fit.
Our tech-enabled search scans thousands of candidates across LatAm, both active and passive. We leverage advanced tools and regional expertise to build a comprehensive talent pool.
We carefully assess 30+ candidates with proven track records. Our rigorous evaluation ensures each professional brings relevant experience from industry-leading companies, aligned to your needs.
Receive a curated selection of 3-4 top candidates with comprehensive profiles. Each includes proven background, key achievements, and expectations—enabling informed hiring decisions.
Top candidates ready for your assessment. We handle interview logistics and feedback collection—ensuring smooth evaluation. Not fully convinced? We iterate until you find the perfect fit.
We manage contracting, onboarding, and payment to your team seamlessly. Our partnership extends beyond hiring—providing retention support and strategic guidance for the long-term growth of your LatAm team.
How to Write an Effective Job Post to Hire Data Management Engineers
Recommended Titles
- Data Engineer
- Data Platform Engineer
- Data Infrastructure Developer
- Information Management Engineer
- Data Integration Specialist
- Data Governance Engineer
Role Overview
- Tech Stack: Skilled in SQL, Snowflake, Python, and ETL tools like Talend or Informatica.
- Project Scope: Design and manage robust data pipelines, storage layers, and governance models.
- Team Size: Join a central data engineering group of 4–6 working across departments.
Role Requirements
- Years of Experience: At least 3 years in enterprise data infrastructure or warehouse roles.
- Core Skills: Data cataloging, schema management, data lineage, and ETL orchestration.
- Must-Have Technologies: Snowflake, SQL, Python, dbt, Informatica/Talend.
Role Benefits
- Salary Range: $95,000 – $150,000 depending on domain complexity.
- Remote Options: Fully remote with synchronous and async data ops workflows.
- Growth Opportunities: Influence data governance strategy in high-scale environments.
Do
- List experience in data architecture, cataloging, and governance
- Include knowledge of metadata management and lineage
- Mention tools like Collibra, Alation, or Informatica
- Highlight collaboration with security and compliance teams
- Use structured and enterprise-grade data language
Don't
- Don’t list ETL roles without governance and architecture focus
- Avoid skipping data cataloging or metadata skills
- Don’t conflate with traditional DBAs
- Refrain from omitting compliance or lineage responsibilities
- Don’t post without mentioning cross-functional alignment
Top Data Management Engineer Interview Questions
Questions to ask Data Management Engineers before hiring
How do you design scalable data architecture?
Expect data lake vs. data warehouse discussion, partitioning strategies, and support for real-time vs. batch pipelines.
What’s your approach to master data management?
Look for version control, data stewardship roles, standardization policies, and integration across business systems.
How do you handle schema evolution in production?
Strong answers include schema registries, backward compatibility checks, and migration strategies.
What tools have you used for data cataloging?
Expect mention of Alation, Collibra, DataHub, or cloud-native catalogs. Look for governance experience too.
How do you monitor data health in your systems?
They should mention freshness checks, anomaly detection, observability dashboards, and automated alerts.
How do you troubleshoot data quality issues in large datasets?
Expect use of validation rules, profiling tools, anomaly detection, and data lineage tracing.
Describe a situation where a data model caused downstream issues.
Look for impact analysis, communication with stakeholders, and normalization or refactoring solutions.
How do you handle inconsistent source data from different systems?
Expect data harmonization strategies, master data management, and reconciliation logic.
What’s your process for resolving data integrity violations?
Expect rollback strategies, transaction isolation troubleshooting, and enforcement of business rules.
How do you manage schema changes across environments?
Look for version control, automated deployment, and rollback plans to ensure data continuity.
Tell me about a BI implementation where the client’s expectations were unclear.
Look for discovery session planning, goal alignment, and phased delivery.
Describe a time you had to change your recommendation based on stakeholder feedback.
Expect flexibility, data revalidation, and updated solution proposals.
How do you manage resistance to BI tool adoption?
Expect onboarding strategies, stakeholder training, and ROI communication.
How do you prioritize competing requirements during BI roadmapping?
Look for frameworks used (e.g., impact vs. effort), facilitation experience, and client co-creation.
What’s your process when client data is incomplete or inconsistent?
Expect pre-analysis audits, documentation, and recommendations for data cleanup plans.
- Overlooking data quality and validation routines
- Fails to document pipeline structure and logic
- Weak understanding of metadata management
- Inconsistent handling of schema changes
- Neglects data access controls and compliance
Build elite teams in record time, full setup in 21 days or less.
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End-to-end remote talent solutions, from recruitment to payroll. Country-compliant throughout LatAm.
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Our recruiting team delivers pre-vetted candidates within a week. Not the perfect match? We iterate until you're satisfied. You control hiring and contracts, while we provide guidance.
Staffing
Our recruiters deliver pre-vetted remote talent in a week. You select the perfect candidate, we manage onboarding, contracts, and ongoing payroll seamlessly.
RPO
Our RPO services deliver flexible talent solutions. From targeted support to full-cycle recruitment, we adapt and scale to meet your hiring goals while you focus on strategic growth.
