Senior Data Engineer

About You

You are a Senior Data Engineer who enjoys building reliable, scalable data platforms and enabling data-driven and AI-powered products. You feel comfortable owning data pipelines end to end, working closely with analytics and AI/Data Science teams, and translating complex data problems into robust technical solutions.
You value clean architecture, performance, and data quality, and you’re curious about AI/ML integrations even if you’re not a model builder. You thrive in collaborative environments and can operate with autonomy while guiding best practices across teams.

You Bring to Applaudo the Following Competencies:

• Bachelor’s degree or higher in Computer Science, Computer Engineering, or related field — or equivalent professional experience.
• 5+ years of experience as a Data Engineer, building and operating production-grade data pipelines.
• Strong expertise in SQL, including advanced joins, CTEs, window functions, and performance tuning.
• Experience designing data models and analytical structures (dimensional models, facts, dimensions, SCDs).
• Hands-on experience building ETL/ELT pipelines using modern orchestration tools (Airflow, Dagster, DBT, or similar).
• Proficiency in Python for data processing and pipeline development (PySpark is a strong plus).
• Solid experience working with cloud platforms (AWS, Azure, or GCP) for data storage and processing.
• Familiarity with data platforms such as Snowflake, Databricks, PostgreSQL, or similar.
• Experience using Git and CI/CD practices as part of a modern data engineering workflow.
• Exposure to supporting AI/Data Science initiatives, such as data enablement for models, embeddings, entity matching, or advanced analytics (nice to have).
• Familiarity with graph databases, embeddings, or AI integrations from a data engineering perspective (nice to have).
• Ability to work independently and collaborate effectively with analysts, ML engineers, and product teams.
• Advanced English proficiency (B2+), able to work with global stakeholders.

You Will Be Accountable for the Following Responsibilities:

• Design, build, and maintain scalable data pipelines and ingestion processes supporting analytics and AI use cases.
• Implement and optimize ETL/ELT workflows with attention to performance, reliability, and cost.
• Design and evolve data models and curated layers to support reporting, analytics, and downstream systems.
• Collaborate with analytics, AI/Data Science, and product teams to understand data requirements and SLAs.
• Support AI and advanced analytics features by providing clean, well-structured, and reliable datasets.
• Apply best practices around data quality, validation, monitoring, and observability.
• Write maintainable, well-documented data code and contribute to shared standards and patterns.
• Participate in architecture discussions and help improve overall data platform design.
• (If senior/lead-leaning) Support or mentor less-experienced data engineers as the team grows.