piso 8vo, Argentina
Live, first seen by us 87 days agoEmployment type in the employer’s posting: Full timeFrom the employer’s posting
We are looking for a seasoned Data Architect to own the data architecture and product delivery strategy for our retail and downstream business.
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.
Design and own end-to-end data architecture from ingestion to consumption
Lead design and delivery of reusable, well-documented data products
Translate local business requirements into architecture decisions aligned with global IT
Drive data quality, lineage, and cataloguing practices
Mentor data engineers and analysts with architectural guardrails
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.
Design and own end-to-end data architecture for retail and downstream data products from ingestion to consumption layer.
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.
Drive data quality, lineage, and cataloguing practices across the full data landscape.
Mentor and guide data engineers and analysts, setting architectural guardrails and best practices.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 87
Up longer than most. Similar jobs usually come down between day 7 and day 55.
Well past Trafigura’s usual: its jobs come down by about day 40.
From 8,361 similar postings that came down, and 24 of Trafigura’s. Coming down is not always a hire.
2 open jobs
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
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
- 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.
- 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.
- 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.
- 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.
- 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.
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.
- 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.
- 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.
- 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.
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
- 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.
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New Data Leadership postings at the employers we follow are up 7% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
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
MUST-HAVE REQUIREMENTS
NICE TO HAVE
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No pay amount identified in the saved description.
piso 8vo, Argentina
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.
No clear work-authorization passage found. Eligibility is unconfirmed.