Data Services Engineer (Strategic Projects)

Join our team as a Data Services Engineer, where you'll play a crucial role in a strategic data transformation initiative for a single enterprise client. You'll work closely with the client to understand their business needs and data landscape, design scalable data models, and drive improvements to internal workflows. This remote-friendly position offers opportunities for learning and development, flexible PTO, 401(k) matching, healthcare coverage, and monthly recharge days.

• Collaborate closely with a single enterprise client to design efficient, accessible data models that unlock real business value.
• Engineer and optimize the ingestion of large volumes of data into cloud data warehouses, ensuring scalability and performance.
• Drive improvements to internal workflows and tooling to increase efficiency and repeatability, serving as a thought partner for client stakeholders.
• You're passionate about clean data architecture, skilled at breaking down complex problems into manageable parts, and you appreciate the long-term value of scalable tooling and repeatable processes
• If you thrive in a fast-paced environment with autonomy, growth potential, and purpose-driven work, this role is for you
• Solid understanding of relational databases and core data warehousing principles
• Self-starter who thrives in autonomous environments and takes ownership of outcomes
• Experience working with BI and visualization tools (e.g., Looker, Tableau, Power BI, or similar)
• Strong data modeling skills, with the ability to design scalable, well-structured models for both analytical and operational use cases
• 2–5 years of experience as a Data Engineer or Analytics Engineer, with strong proficiency in SQL and Python
• Proven experience designing, building, and maintaining cloud data warehouses (e.g., BigQuery, Snowflake, Redshift)
• Strong analytical thinking and problem-solving abilities
• Naturally curious, with a passion for learning and applying new tools and technologies
• Hands-on experience with Google Cloud Platform (GCP), including core services such as BigQuery
• Experience with workflow orchestration platforms like Airflow
• Experience with transformation and modeling tools such as dbt or Google Cloud Dataform
• Exposure to machine learning workflows, including model development, training, deployment, or productionization
• Experience working with or within large enterprise organizations