Designs and implements scalable data lakehouse platforms on GCP, including BigQuery, GCS, BigLake, and Dataplex. Leads real-time and batch data pipeline development, data governance, metadata management, security, and performance optimization. Partners with clients and stakeholders to translate business needs into architecture, leads technical teams, mentors engineers, and provides hands-on solutioning and technical advisory support.
About Egen:
Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results. If this describes you, we want you on our team.
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Responsibilities
- Be part of the end-to-end architecture, design, and implementation of scalable Data Lakehouse solutions on Google Cloud Platform (GCP) using BigQuery, GCS, BigLake, and Dataplex
- Collaborate directly with customers to understand business goals, data challenges, and technical requirements; translate them into robust architectural blueprints and actionable plans
- Design and implement data pipelines supporting both real-time and batch ingestion using modern orchestration and streaming frameworks
- Establish and enforce best practices for data cataloging, metadata management, lineage, and data quality across multiple systems
- Define and implement data security, access control, and governance models in compliance with enterprise and regulatory standards
- Serve as the technical lead for project teams - mentoring engineers, reviewing solutions, and ensuring architectural consistency across deliverables
- Balance strategic architecture discussions with hands-on solutioning, POCs, and deep dives into data pipelines or performance tuning
- Partner with stakeholders, cloud architects, and delivery leads to drive solution adoption, scalability, and long-term maintainability
- Represent the company as a trusted technical advisor in client engagements - clearly articulating trade-offs, best practices, and recommendations
Qualifications
- 6+ years of progressive experience in Software Engineering and Data Platform development, with 5+ years architecting data platforms on GCP and/or Databricks
- Proven hands-on experience designing and deploying Data Lakehouse platforms with data products and medallion architectures
- Strong understanding of data ingestion patterns (real-time and batch), ETL/ELT pipeline design, and data orchestration using tools such as Airflow, Pub/Sub, or similar frameworks
- Expertise in data modeling, storage optimization, partitioning, and performance tuning for large-scale analytical workloads
- Experience implementing data governance, security, and cataloging solutions (Dataplex, Data Catalog, IAM, or equivalent)
- Excellent communication and presentation skills - able to confidently engage with technical and non-technical stakeholders and guide clients through solution decisions
- Demonstrated ability to lead by example in mixed teams of engineers, analysts, and architects, balancing architectural vision with hands-on delivery
- Nice to have: Experience with Databricks (Delta Lake, Unity Catalog) and hybrid GCP-Databricks data architectures
- Strong problem-solving mindset, curiosity to explore new technologies, and ability to “zoom out” for architecture discussions and “zoom in” for code-level troubleshooting
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