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
Candela is a data generalist delivering actionable insights from structured analysis.
- ETL Processes
- Data Dashboards
- Quantitative Research
- Forecasting Models
- Data Literacy
Matías is a data specialist streamlining systems through clean and efficient models.
- Data Warehousing
- ETL Processes
- Trend Reporting
- Dashboards
- Real-Time Data
Agustina excels as a skilled data analyst, known for insightful analysis and sharp precision.
- Power BI
- Excel
- A/B Testing
- Data Visualization
- SQL
Francisca, a skilled data scientist, excels in part-time roles with precision and insight.
- Python
- Statistics
- Feature Engineering
- Machine Learning
- Data Cleaning
Mateo is a data analyst delivering structured insights for confident business actions.
- Exploratory Data Analysis
- Power BI & Tableau
- Forecasting Models
- SQL Queries
- Data Reporting
Juliana is a Data thinker who enables smarter decisions through thoughtful analysis.
- Data Analysis
- SQL
- Data Visualization
- Reporting
- Forecast Modeling
Sofía is a Data professional turning metrics into insights that support better decisions.
- Data Analysis
- Data Visualization
- SQL
- Business Intelligence
- Reporting
"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”
Lupa's Proven Process
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.
Reviews
"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”
“We scaled our first tech team at record speed with Lupa. We couldn’t be happier with the service and the candidates we were sent.”
"Recruiting used to be a challenge, but Lupa transformed everything. Their professional, agile team delivers top-quality candidates, understands our needs, and provides exceptional personalized service. Highly recommended!"
“Lupa has become more than just a provider; it’s a true ally for Pirani in recruitment processes. The team is always available to support and deliver the best service. Additionally, I believe they offer highly competitive rates and service within the market.”
"Highly professional, patient with our changes, and always maintaining clear communication with candidates. We look forward to continuing to work with you on all our future roles."
“Lupa has been an exceptional partner this year, deeply committed to understanding our unique needs and staying flexible to support us. We're excited to continue our collaboration into 2025.”
"What I love about Lupa is their approach to sharing small, carefully selected batches of candidates. They focus on sending only the three most qualified individuals, which has already helped us successfully fill 7 roles.”
"We hired 2 of our key initial developers with Lupa. The consultation was very helpful, the candidates were great and the process has been super fluid. We're already planning to do our next batch of hiring with Lupa. 5 stars."
"Working with Lupa for LatAm hiring has been fantastic. They found us a highly skilled candidate at a better rate than our previous staffing company. The fit is perfect, and we’re excited to collaborate on more roles."
"We compared Lupa with another LatAm headhunter we found through Google, and Lupa delivered a far superior experience. Their consultative approach stood out, and the quality of their candidates was superior. I've hired through Lupa for both of my companies and look forward to building more of my LatAm team with their support."
“We’ve worked with Lupa on multiple roles, and they’ve delivered time and again. From sourcing an incredible Senior FullStack Developer to supporting our broader hiring needs, their team has been proactive, kind, and incredibly easy to work with. It really feels like we’ve gained a trusted partner in hiring.”
Working with Lupa was a great experience. We struggled to find software engineers with a specific skill set in the US, but Lupa helped us refine the role and articulate our needs. Their strategic approach made all the difference in finding the right person. Highly recommend!
Lupa goes beyond typical headhunters. They helped me craft the role, refine the interview process, and even navigate international payroll. I felt truly supported—and I’m thrilled with the person I hired. What stood out most was their responsiveness and the thoughtful, consultative approach they brought.
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.
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.
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.
Book a Free ConsultationWhy We Stand Out From Other Recruiting Firms
From search to hire, our process is designed to secure the perfect talent for your team
Local Expertise
Tap into our knowledge of the LatAm market to secure the best talent at competitive, local rates. We know where to look, who to hire, and how to meet your needs precisely.
Direct Control
Retain complete control over your hiring process. With our strategic insights, you’ll know exactly where to find top talent, who to hire, and what to offer for a perfect match.
Seamless Compliance
We manage contracts, tax laws, and labor regulations, offering a worry-free recruitment experience tailored to your business needs, free of hidden costs and surprises.
Lupa will help you hire top talent in Latin America.
Book a Free Consultation
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
