Jobs at Entrada

Design, build, and optimize scalable data pipelines, warehouses, lakes, and processing systems for analytics and business intelligence. Ensure data quality, security, reliability, and cost efficiency while collaborating with data scientists, analysts, and engineers. Maintain technical documentation, support Databricks solutions, and apply emerging data engineering technologies. The role requires strong programming, SQL, ETL, orchestration, data modeling, cloud, and big data expertise.

Design and scale Databricks Genie conversational data interfaces, including Genie Spaces, semantic layers, SQL guidance, testing, fine-tuning, and external integrations. Build optimized Python, SQL, and PySpark pipelines in Delta Lake, support LLM-based metadata enrichment and semantic optimization, and translate business requirements into reliable data models. Collaborate with stakeholders and maintain high standards for accuracy, performance, and governed enterprise data access.

Develop and execute sales strategies for consulting services, identify and qualify target accounts, manage opportunities from lead through close, and grow relationships with direct clients and technology partners. The role involves pipeline management, prospecting, targeted messaging, partner collaboration, market-facing activities, and representing Entrada at client meetings and industry events. Candidates should build credibility in data and analytics and use HubSpot, LinkedIn, AI, and other prospecting tools.

Design, deploy, and optimize machine learning models and infrastructure using Databricks. Lead end-to-end model development, including data preparation, deployment, monitoring, and production scaling. Collaborate with data scientists, engineers, business stakeholders, and clients to deliver technical solutions. Mentor junior team members and apply advances in machine learning, NLP, computer vision, and MLOps to solve complex business problems.

Design and lead scalable data architectures for client organizations, covering data lakes, warehouses, databases, integrations, governance, security, and quality. Translate business requirements into architecture solutions, optimize cloud and on-premise systems for performance and cost, guide engineering teams, document designs, and maintain expertise in Databricks and modern data technologies. The role requires up to 20% travel to client sites.

Lead the architecture and development of scalable Databricks data solutions for global clients. Build PySpark pipelines, migrate legacy warehouses to Delta Lake, optimize Spark performance and costs, implement governance with Unity Catalog, and establish code quality and CI/CD standards. Advise stakeholders on data strategy, mentor engineers, and deliver modern Lakehouse architectures using cloud platforms and contemporary orchestration tools.

Designs and oversees enterprise data architectures spanning databases, warehouses, lakes, integrations, and cloud environments. Translates business requirements into scalable, secure, and cost-efficient solutions; establishes data modeling, governance, quality, metadata, and security practices; guides engineers and analysts; optimizes infrastructure; and maintains architecture documentation. Requires extensive Databricks, data engineering, big data, cloud, and stakeholder leadership experience.

Analyze complex datasets, develop and deploy predictive models, collaborate with data engineers and product teams, communicate insights through visualizations and presentations, and evaluate emerging data science and AI techniques. The role focuses on customer segmentation, demand forecasting, recommendation systems, data quality, and integrating machine learning models into production systems using Databricks and related technologies.