Springml, Inc.
From Springml, Inc.'s careers page
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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.
Want to learn more about life at Egen? Check out these resources in addition to the job description.
Meet Egen
Life at Egen
Culture and Values at Egen
Career Development at Egen
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
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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