• Collaborates and pairs with product team members (UX, engineering, and product management) to create secure, reliable, scalable software solutions • Documents, reviews and ensures that all quality and change control standards are met • Writes custom code or scripts to automate infrastructure, monitoring services, and test cases • Works with vendors and partners for the successful implementation of critical tooling and platforms • Creates meaningful dashboards, logging, alerting, and responses to ensure that issues are captured and addressed proactively • Contributes to enterprise-wide tools to drive destructive testing, automation, and engineering empowerment • Evaluates new technologies for adoption across the enterprise • Participates in and leads review board sessions to drive consistency across the enterprise • Fills in on product teams for engineers who are out of the office • Fields questions from engineers, product teams, or support teams • Monitors tools and participates in conversations to encourage collaboration across product teams • Provides application support for software running in production • Acts as a technical escalation point for the engineers on the team • Provides leadership, mentoring, and coaching to Software Engineers • Attracts, retains, and develops top talent to build a world class Software Engineering Team • Conducts annual and mid-year reviews by reviewing individual development plans and team feedback • Fosters collaboration with team members to drive consistency across product teams, and finds opportunities to expose engineers to career interests • Acts as a proponent of modern software development practices • Guides team members in strategy, alignment, analysis, and execution tasks within and across product teams • Participates in and contributes to learning activities around modern software design and development core practices (communities of practice) • Learns, through reading, tutorials, and videos, new technologies and best practices being used within other technology organizations • Builds relationships with technology leaders at other companies to learn best practices and elegant solutions to common problems

We are building the next generation of our enterprise data platform and are seeking a Cloud Data Engineer to architect, develop, and optimize large-scale, cloud-native data warehousing and ETL pipelines on AWS. You will be responsible for designing our data warehouses, implementing scalable AWS-based ingestion and transformation pipelines, and enabling high-quality analytics and BI across the organization. This role is ideal for someone with deep hands-on engineering expertise in cloud data ecosystems, data modeling, analytics enablement, and modern ETL patterns ESSENTIAL DUTIES AND RESPONSIBILITIES - Design and implement AWS-native ETL/ELT pipelines using services such as: - AWS Glue - AWS Lambda - Amazon MWAA / Apache Airflow - Step Functions - S# / Lake Formation - Architect and maintain data warehouses using Amazon Redshift (or Snowflake/Databricks on AWS). - Build robust data ingestion patterns including incremental loads, partitioning strategies, and schema evolution handling. - Ensure pipelines are secure, observable, cost‑efficient, and reliable in production environments. REQUIRED SKILLS AND ABILITIES - Strong understanding of data warehousing concepts and best practices - Expertise in SQL and query optimization for large-scale datasets - Proficiency in cloud data platforms (AWS preferred) and associated services (Glue, Lambda, Airflow, S3, etc.) - Strong programming skills (e.g., Python, C#, or similar) for ETL development and automation - Experience designing and implementing scalable ETL/ELT pipelines - Knowledge of modern data formats (Parquet, JSON, ORC) and file-based processing - Experience with data modeling (star/snowflake schemas, fact/dimension design) - Familiarity with data governance, lineage, and security in cloud environments - Experience integrating AI/LLM tools into engineering workflows is a plus - Strong written and verbal communication skills - Ability to manage multiple priorities and meet deadlines in a fast-paced environment KNOWLEDGE, EXPERIENCE, AND/OR EDUCATION REQUIREMENTS - Bachelor’s degree preferred but not required - - In lieu of a degree, equivalent experience in data engineering, computer science, or related field - 5–8 years of experience in data engineering or data warehousing - Hands-on experience with cloud data platforms (AWS strongly preferred) - Experience building and maintaining large-scale data pipelines and warehouses - Experience working with BI tools such as Tableau, Power BI, Quick Sight or similar - Experience with applied AI in data workflows is a plus Disclaimer: This job description is not intended to be an exhaustive list of all duties, responsibilities, or qualifications associated with the job. Management reserves the right to modify or reassign job duties as business needs evolve. #LI-RZ1 #LI-Remote Empyrean is an Equal Opportunity Employer: including disability and protected veteran status

• Conduct requirements analysis with the client • Design and optimize data architectures, including interfaces between systems • Support the implementation of a data warehouse architecture from concept through data validation • Take on lead responsibilities and manage own clients

• Build and scale high-throughput streaming pipelines • Design, implement, and operate pipelines ingesting 400M+ monthly MLS updates across 350+ integrations using Airflow, Spark Streaming, Kafka, and Iceberg • Model and deliver high-quality, production-grade real estate datasets • Develop and maintain datasets that power core product experiences • Strengthen data quality and observability • Implement and improve data quality checks, monitoring, and alerting • Leverage AI to improve data operations • Contribute to AI-driven tooling that helps triage, debug, and resolve data quality issues