Desarrollador ETL
Also searched as: Ingeniero de datos · Ingeniera de datos · Data engineer · ETL
Code 2521.5.1
This role has no official English translation yet; it is shown in Spanish.
What does a Desarrollador ETL do?
The ETL / data engineer (ingeniero de datos or data engineer) builds and maintains the pipelines that move data from source systems into reports, lakes or models. In Chile the ad says ingeniero de datos or data engineer; ETL names the work, not an org-chart title. Use this Job Dictionary profile to separate it from the analyst who consumes dashboards and the scientist who models on top.
How critical is this role
Connects strategy with day-to-day execution.
Maintains the pipelines feeding reports and models. When they break with nobody to fix them, the business decides on stale data without noticing.
A reference range based on our own search work in Chile, not a figure from a published study. It shifts with the salary offered, the location and any exclusivity requirement.
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Essential skills
Knowledge
- API Application Programming Interface
- APIs JSON
- APIs REST
- Apache Spark
- Data Factory (ETL processes)
- Database management
- GitHub
- Google BigQuery
- JavaScript Object Notation (JSON)
- Linux
- Linux Shell Scripting Automations
- MySQL
- Non-relational Databases
- Object Oriented Programming
- Oracle Relational Database
- PostgreSQL
- Python
- Python (computer programming)
- Relational Databases
- Representational State Transfer REST
- SQL Data Warehouse
- SQL Server
- task algorithmisation
- data storage
- data warehouse
- web analytics
- information architecture
- database
- information categorisation
- communication
- unstructured data
- information security strategy
- information structure
- data mining
- information extraction
- product data management
- ICT security legislation
- data models
- online analytical processing
- computer programming
- cloud technologies
Skills and competences
- store digital data and systems
- analyse big data
- analyse business requirements
- implement ICT risk management
- apply information security policies
- implement data quality processes
- apply ICT systems theory
- consult information sources
- create database diagrams
- create software design
- create data models
- create solutions to problems
- define database physical structure
- develop automated migration methods
- develop information security strategy
- design database in the cloud
- design database backup specifications
- design database scheme
- design application interfaces
- design user interface
- perform data mining
- establish data processes
- create data sets
- manage ICT data architecture
- manage database
- manage data
- manage digital documents
- manage ICT data classification
- manage standards for data exchange
- manage cloud data and storage
- manage data collection systems
- identify software for warehouse management
- integrate ICT data
- handle data samples
- operate relational database management system
- migrate existing data
- normalise data
- process data
- perform data analysis
- perform data cleansing
- write database documentation
- collect ICT data
- use databases
- utilise regular expressions
- use back-up and recovery tools
- use query languages
- use data processing techniques
Transversal competences
- address problems critically
- information confidentiality
- meet deadlines
- define data quality criteria
- data quality assessment
- manage quantitative data
- manage schedule of tasks
- interpret current data
- think analytically
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What to assess for this role
Assess pipeline design, data quality, real incidents and whether the role is the only one who knows the pipes (single-point risk).
See psychometric assessmentLo que más nos preguntan
Common questions about this role when you are hiring or writing the job profile.
- What does an ETL / data engineer do?
- Designs, runs and repairs the pipelines that feed reports and models: extract, transform, load and freshness monitoring.
- Data engineer vs analyst or data scientist?
- The data engineer gets data in clean and on time. The analyst interprets it. The scientist models on top. Mixing them in the ad attracts people who will not maintain the pipeline.
- When does headhunting make sense for this role?
- When one person holds the critical pipelines, the active market does not yield (uncommon stack, regulated industry) or an internal replacement would take months to learn the source map.
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Sources
This service uses the ESCO classification of the European Commission and the Mapha Taxonomy developed by OTIC SOFOFA (CC BY 4.0), in an adapted version. Group codes come from the ILO's ISCO-08. See sources and licences