Quick Summary
Gross salary of $90,000. Fully remote work arrangement. Opportunity to work on complex data engineering, analytics, Power BI, cloud, and AI-driven initiatives.
This role offers the opportunity to combine advanced data engineering, analytics, and business intelligence in a highly technology-driven environment. You will build and maintain scalable data pipelines while creating reliable models that support critical reporting and decision-making. The position combines hands-on work with Python, SQL, dbt, Airflow, cloud data platforms, and Power BI. You will translate complex business needs into practical analytics solutions and help strengthen data quality across the organization. Working with international teams and client stakeholders, you will contribute to modern data and AI-enabled initiatives. The role is ideal for a senior data professional who enjoys ownership, continuous learning, and solving complex technical challenges.
- Build, maintain, and enhance data pipelines and transformation workflows using dbt, Python, and Airflow DAGs.
- Develop clean, reliable, reusable data models and analytics datasets to support reporting and business intelligence.
- Use SQL and modern data warehouse technologies to investigate data, troubleshoot issues, and implement effective transformations.
- Design and maintain Power BI dashboards, reports, semantic models, and DAX measures, with attention to performance and usability.
- Translate business requirements into scalable data models, reporting solutions, and analytics workflows.
- Perform data analysis, validation, reconciliation, and ongoing data quality checks to ensure reliable outputs.
- Debug and support existing data pipelines and analytics solutions, identifying opportunities for continuous improvement.
- Explore and apply AI tools to improve productivity and efficiency across daily data engineering and analytics activities.
- Collaborate effectively with international teams and client stakeholders while taking ownership of deliverables in a fast-paced environment.
Requirements
~1 min read- 10+ years of professional experience in the data domain.
- Strong SQL and data analysis capabilities, with the ability to investigate complex datasets and identify data quality or transformation requirements.
- Strong Python proficiency for building data pipelines and managing complex transformations and integrations.
- Hands-on experience with dbt and/or modern ELT and data transformation practices.
- Solid understanding of data modeling, including dimensional modeling, fact and dimension structures, and analytics datasets.
- Experience working with modern cloud data warehouses, preferably Snowflake.
- Strong hands-on Power BI experience, including data modeling, DAX, dashboard development, semantic models, and performance optimization.
- Experience debugging, maintaining, and supporting data pipelines and analytics solutions.
- Ability to quickly understand unfamiliar datasets, identify relationships, and determine appropriate transformation requirements.
- Excellent communication and client-facing skills, combined with exceptional attention to detail.
- Ability to work independently with limited supervision while collaborating effectively within a team.
- Resilience, emotional intelligence, adaptability, and an agile delivery mindset.
- Strong engineering-oriented mindset, with a clear understanding of the distinction between coding and engineering.
- Familiarity with cloud-native technologies or AI coding assistants is a plus.
- Advanced spoken English and advanced Spanish are required for global collaboration and client-facing responsibilities.
What We Offer
~1 min readLocation & Eligibility
Listing Details
- Posted
- September 29, 2026
- First seen
- September 29, 2026
- Last seen
- September 29, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 68%
- Scored at
- September 29, 2026
Signal breakdown
Stay ahead of the market
Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.
No spam. Unsubscribe at any time.