• Design, build, and maintain scalable ETL/ELT pipelines using Databricks and Spark • Design and maintain processes to integrate and transform source data into curated, analytics-ready data layers • Collaborate with product, analytics, and engineering teams to translate business needs into data solutions • Maintain data documentation including data dictionaries and lineage • Work with SQL Server, including querying and managing data • Leverage AI-enabled tools and analytics to enhance decision-making, improve efficiency, and drive measurable business outcomes when appropriate. • Apply sound judgment and ethical standards when using AI, ensuring accuracy, data privacy, and responsible human-in-the-loop oversight. • Other duties as assigned

• Lead the design and delivery of Built’s application-facing data products platform, including product surfaces, backend services, APIs, frontend flows, and reusable patterns. • Build full-stack customer experiences using TypeScript, React, Node.js, Python, and related technologies. • Partner with Product to shape ambiguous ideas into useful customer workflows, challenge low-value requirements, and offer practical alternatives. • Turn data science prototypes, analytics concepts, and platform capabilities into production-grade product experiences. • Bring strong software engineering practices into a data-heavy team through technical design, code review, mentoring, testing, and delivery patterns. • Help data engineers take on more software engineering work across frontend, backend, APIs, product decomposition, and production readiness. • Collaborate across Built where data products integrate with application surfaces, platform capabilities, agents, or customer workflows. • Use customer signals, usage data, product feedback, support issues, and discovery learnings to guide engineering decisions.

Role Description The Data Engineer V leads the design, development, and optimization of scalable data pipelines and analytics platforms. This role partners closely with product, analytics, and engineering teams to deliver high-quality, reliable data solutions that drive business insights. - Design, build, and maintain scalable ETL/ELT pipelines using Databricks and Spark - Design and maintain processes to integrate and transform source data into curated, analytics-ready data layers - Collaborate with product, analytics, and engineering teams to translate business needs into data solutions - Maintain data documentation including data dictionaries and lineage - Work with SQL Server, including querying and managing data - Leverage AI-enabled tools and analytics to enhance decision-making, improve efficiency, and drive measurable business outcomes when appropriate - Apply sound judgment and ethical standards when using AI, ensuring accuracy, data privacy, and responsible human-in-the-loop oversight - Other duties as assigned Qualifications - Proficient programming / scripting in Python, SQL - Proficiency in cloud data platforms (Azure preferred) - Experience building data pipelines that ingest, transform, and load source data into curated data models - Experience with data pipeline orchestration and workflow tools - Strong working knowledge of Git-based version control workflows - Strong proficiency in SQL Server including query optimization and performance tuning - Demonstrated ability to scope and deliver projects within timelines - Ability to collaborate effectively with cross-functional teams to deliver data-driven solutions - Strong problem-solving skills and operates with high autonomy and ownership - 8 years of relevant experience Requirements - Experience in programming / scripting in PySpark, Databricks SQL, DAX - Experience with data modeling techniques (star schema, dimensional modeling) - Experience in creating PowerBI reports - Experience delivering projects within Agile/Scrum environments - Experience in communicating complex technical concepts to non-technical stakeholders - Experience following existing coding standards - Bachelor’s degree in Computer Science or relevant field Benefits - Medical Insurance - Life Insurance - Dental Insurance - Vision Insurance - PTO - Paid Parental Leave - Paid Holidays - Short Term Disability - Long Term Disability - 401K - Educational Assistance

Role Description We are seeking a skilled Data Engineer to join our team and help design, build, and maintain scalable data pipelines and cloud-based data solutions. The ideal candidate has strong experience working with Python, SQL, cloud-based data platforms, and modern data engineering practices. This role requires a proactive professional who enjoys solving complex data challenges and collaborating across teams to deliver reliable and scalable data solutions. Qualifications - 5+ years of professional experience in Data Engineering or related roles. - Strong Python programming skills, including experience with Pandas and NumPy. - Advanced SQL skills and experience working with relational databases. - Experience designing, building, and maintaining ETL/ELT pipelines. - Hands-on experience with AWS data platforms, including Amazon S3 and Data Lake architectures. - Familiarity with AWS services such as Glue, Athena, Lambda, Step Functions, and/or Redshift. - Experience integrating and consuming REST APIs. - Experience working with time-series datasets. - Knowledge of analytical data formats including Parquet, CSV, and JSON. - Experience using Docker-based development environments. - Proficiency with Git and collaborative software development practices. - Understanding of data quality, validation, monitoring, and observability concepts. - Strong problem-solving, attention to detail and analytical skills. - Ability to work independently in a remote environment. - Effective collaboration skills. - Professional English communication skills. Requirements - Experience in energy, power, electricity, or trading markets (Nice to Have). - Experience supporting machine learning workflows and data science teams (Nice to Have). Key Responsibilities - Design, develop, and maintain scalable ETL/ELT pipelines. - Build and optimize data ingestion processes from multiple sources, including REST APIs, databases, and external systems. - Design, build, and optimize data ingestion and processing workflows using Python and SQL. - Develop and maintain data solutions leveraging AWS services and Data Lake architectures. - Work with structured and semi-structured data formats, including Parquet, CSV, and JSON. - Implement data validation, monitoring, and quality controls. - Optimize data models, queries, and storage solutions for performance and scalability. - Collaborate with cross-functional teams to deliver reliable and scalable data solutions. - Support analytics, reporting, and machine learning use cases. Company Description Fully Remote Opportunity Mexico Candidates Only