Data Architect
Locationpiso 8vo, Argentina
Typefull-time
SeniorityLead
Experience10+ yrs
Company size10,000+ people
PostedAug 12, 2026 · 2mo ago
Verified live20h ago
At a glanceSummarised by Seekless from the posting.
10+ years of experience in data architecture, data engineering, or data platform roles, with at least 5 years in a senior architecture capacity
Deep hands-on expertise with Databricks: Lakehouse design, Delta Lake, Unity Catalog, and data pipeline orchestration
Strong cloud platform experience across AWS and Azure storage, computing, orchestration, and governance services
Proven track record designing and delivering data products governed, business-ready data assets, not just pipelines
Solid command of data modeling techniques: dimensional modeling, Data Vault, or equivalent
Hands-on experience with Apache Airflow, designing, deploying, and maintaining complex workflow orchestration at scale
Hands-on experience with Apache Kafka event streaming architecture, topic design, producers/consumers, and real-time data pipeline patterns
Solid dbt experience data transformation layer design, testing frameworks, documentation practices, and integration with modern data stacks
Strong SQL expertise, complex query writing, performance tuning, and data modeling applied directly in analytical and operational contexts
Python proficiency for data management, scripting, pipeline development, data wrangling, and automation across the data stack
Experience working across global and local IT structures, navigating enterprise standards while addressing regional business needs
Strong stakeholder engagement skills, able to communicate architectural decisions clearly to both technical peers and business leaders
Demonstrated delivery in complex, multi-stakeholder environments with measurable, business-oriented outcomes
Hands-on Snowflake experience: data sharing, warehousing patterns, or hybrid Snowflake/Databricks architectures
Familiarity with data mesh principles and domain-oriented data product ownership models
Knowledge of data governance frameworks and cataloguing tools (e.g., Azure Purview, Collibra, Alation)
Experience in retail, trading, energy, or commodity-intensive industries
Background in BI/analytics layer delivery (Power BI, Qlik, Tableau) and the data architecture that supports it
Skills
Databricks
Unity Catalog
Delta Live Tables
AWS
S3
Glue
Redshift
Lake Formation
Azure
ADLS
Synapse
ADF
Purview
Apache Airflow
Apache Kafka
dbt
SQL
Python
Snowflake
Collibra
Alation
Power BI
Qlik
Tableau
ABOUT THE ROLE
We are looking for a seasoned Data Architect to own the data architecture and product delivery strategy for our retail and downstream business. Operating at the intersection of local business insight and global IT strategy, you will design scalable, well-governed data platforms that translate commercial needs into robust, business-ready data products.
You will work closely with both business and IT stakeholders bridging local operational context with the global data landscape and remain accountable for the architectural quality, reliability, and business relevance of every data product you deliver.
TECHNOLOGY STACK
Must-have: Databricks (Lakehouse, Unity Catalog, Delta Live Tables), AWS (S3, Glue, Redshift, Lake Formation), Azure (ADLS, Synapse, ADF, Purview), Apache Airflow, Apache Kafka, dbt, SQL and Python.
Nice to have: Snowflake and other modern data platform and orchestration tooling
WHAT YOU WILL DO
•
Design and own end-to-end data architecture for retail and downstream data products from ingestion to consumption layer.
•
Define data modeling standards, platform patterns, and architectural principles across the data ecosystem.
•
Lead the design and delivery of data products, ensuring they are reusable, well-documented, and fit for business consumption.
•
Translate local business requirements into architecture decisions aligned with the global IT strategy and data governance framework.
•
Act as the technical bridge between business stakeholders and global IT, ensuring local context is reflected in platform design.
•
Drive data quality, lineage, and cataloguing practices across the full data landscape.
•
Evaluate and recommend new data technologies, architectural patterns, and tooling approaches.
•
Mentor and guide data engineers and analysts, setting architectural guardrails and best practices.
•
Engage with global data and IT teams to align on standards, tooling roadmap, and delivery priorities.
MUST-HAVE REQUIREMENTS
•
10+ years of experience in data architecture, data engineering, or data platform roles, with at least 5 years in a senior architecture capacity.
•
Deep hands-on expertise with Databricks: Lakehouse design, Delta Lake, Unity Catalog, and data pipeline orchestration.
•
Strong cloud platform experience across AWS and Azure storage, computing, orchestration, and governance services.
•
Proven track record designing and delivering data products governed, business-ready data assets, not just pipelines.
•
Solid command of data modeling techniques: dimensional modeling, Data Vault, or equivalent.
•
Hands-on experience with Apache Airflow, designing, deploying, and maintaining complex workflow orchestration at scale.
•
Hands-on experience with Apache Kafka event streaming architecture, topic design, producers/consumers, and real-time data pipeline patterns.
•
Solid dbt experience data transformation layer design, testing frameworks, documentation practices, and integration with modern data stacks.
•
Strong SQL expertise, complex query writing, performance tuning, and data modeling applied directly in analytical and operational contexts.
•
Python proficiency for data management, scripting, pipeline development, data wrangling, and automation across the data stack.
•
Experience working across global and local IT structures, navigating enterprise standards while addressing regional business needs.
•
Strong stakeholder engagement skills, able to communicate architectural decisions clearly to both technical peers and business leaders.
•
Demonstrated delivery in complex, multi-stakeholder environments with measurable, business-oriented outcomes.
NICE TO HAVE
•
Hands-on Snowflake experience: data sharing, warehousing patterns, or hybrid Snowflake/Databricks architectures.
•
Familiarity with data mesh principles and domain-oriented data product ownership models.
•
Knowledge of data governance frameworks and cataloguing tools (e.g., Azure Purview, Collibra, Alation).
•
Experience in retail, trading, energy, or commodity-intensive industries.
•
Background in BI/analytics layer delivery (Power BI, Qlik, Tableau) and the data architecture that supports it.