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What Your Success Will Look Like
Evaluate and improve data quality, completeness, and consistency across 30+ databases, applications, platforms, and APIs.
Design and build Scorpion's analytical data platform, creating a trusted source of truth for business and client data.
Develop and maintain scalable data pipelines that efficiently move data from operational systems into the analytical platform.
Help teams transition from querying production databases directly to using trusted analytical data sources.
Design data access patterns that enable AI agents and applications to quickly retrieve relevant client and business information.
Build secure, scalable solutions that deliver client context and business insights to internal applications and AI-powered experiences.
Define, monitor, and improve service level agreements (SLAs) for data freshness, availability, reliability, and performance.
Partner with engineering, product, and data science teams to establish data standards, governance practices, and data contracts.
Continuously improve the scalability, performance, and reliability of Scorpion's data ecosystem.
Who You Are And What You Bring
EducationBachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field, or equivalent practical experience.
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field, or equivalent practical experience.
Experience7+ years of data engineering experience, including designing and operating production-scale analytical data platforms.Experience building scalable data pipelines, analytical systems, and data platforms in modern cloud environments.Experience integrating and unifying data from multiple systems into trusted, business-ready analytical platforms.Experience supporting data access and consumption patterns for applications, analytics, machine learning, or AI-powered solutions.Experience designing scalable data models that support analytics, reporting, and AI-driven applications.Experience establishing data governance standards, data contracts, and documentation practices across teams.
7+ years of data engineering experience, including designing and operating production-scale analytical data platforms.
Experience building scalable data pipelines, analytical systems, and data platforms in modern cloud environments.
Experience integrating and unifying data from multiple systems into trusted, business-ready analytical platforms.
Experience supporting data access and consumption patterns for applications, analytics, machine learning, or AI-powered solutions.
Details
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field, or equivalent practical experience.
7+ years of data engineering experience, including designing and operating production-scale analytical data platforms.
Experience building scalable data pipelines, analytical systems, and data platforms in modern cloud environments.
Experience integrating and unifying data from multiple systems into trusted, business-ready analytical platforms.
Experience supporting data access and consumption patterns for applications, analytics, machine learning, or AI-powered solutions.
Experience designing scalable data models that support analytics, reporting, and AI-driven applications.
Experience establishing data governance standards, data contracts, and documentation practices across teams.
Data Processing & Lakehouse TechnologiesDeep expertise with Databricks, Delta Lake, and Apache Spark for large-scale data processing, streaming ingestion, and data transformation.
Deep expertise with Databricks, Delta Lake, and Apache Spark for large-scale data processing, streaming ingestion, and data transformation.
Data Warehousing & AnalyticsExperience working with Snowflake, BigQuery, ClickHouse, Azure Synapse, or similar analytical database technologies.
Experience working with Snowflake, BigQuery, ClickHouse, Azure Synapse, or similar analytical database technologies.
Programming & Query Languages: Advanced SQL skills, including query optimization, execution planning, and performance tuning.Strong Python skills for data pipeline development, automation, transformation, and integration with production systems.
Our Scorpion Values
Winning Mindset: When our clients win, we win.
Genuine Care: We only succeed when we are truly invested in our clients and each other.
Unmatched Results: We deliver more than expected–and then some–driving the best results and impacting lives.
Constant Improvement: We believe there is always a better way. We learn we ask “What if?” we build and then do it again.
Unbeatable Teamwork: We come from different backgrounds but have the same vision. We only get there by doing it together, as a team.
Compensation
The base salary range is $155,000 (entry-level) - $185,000 (highly experienced), exclusive of fringe benefits. If you are hired at Scorpion, your final base salary compensation will be determined based on factors such as geographic location, skills, education, and/or experience. Additionally, we believe in the importance of pay equity and consider the internal equity of our current team members as a part of any final offer. Please keep in mind that the range mentioned above is the total salary range for the role. Hiring at the maximum of the range would not be typical in order to allow for future & continued salary growth.
The compensation package may also include incentive compensation opportunities in the form of discretionary bonuses or commissions.
Our Benefits
100% employer-paid medical, dental, and vision insurance
Flexible paid time off, so you can rest, relax, and recharge away from work
Paid parental leave
Paid cell phone and service
Remote office allowance
Professional development and development courses
Regular manager check-ins to drive performance and career growth through Lattice
Experience designing scalable data models that support analytics, reporting, and AI-driven applications.
Experience establishing data governance standards, data contracts, and documentation practices across teams.
Technical SkillsData Processing & Lakehouse TechnologiesDeep expertise with Databricks, Delta Lake, and Apache Spark for large-scale data processing, streaming ingestion, and data transformation.Data Warehousing & AnalyticsExperience working with Snowflake, BigQuery, ClickHouse, Azure Synapse, or similar analytical database technologies.Programming & Query Languages: Advanced SQL skills, including query optimization, execution planning, and performance tuning.Strong Python skills for data pipeline development, automation, transformation, and integration with production systems.Data Pipeline & Orchestration ToolsExperience building and managing data pipelines using dbt, Airflow, Prefect, or similar orchestration and transformation tools.Architecture & SecurityStrong understanding of lakehouse architecture, data partitioning strategies, metadata management, and data security best practices.
Data Processing & Lakehouse TechnologiesDeep expertise with Databricks, Delta Lake, and Apache Spark for large-scale data processing, streaming ingestion, and data transformation.
Deep expertise with Databricks, Delta Lake, and Apache Spark for large-scale data processing, streaming ingestion, and data transformation.
Data Warehousing & AnalyticsExperience working with Snowflake, BigQuery, ClickHouse, Azure Synapse, or similar analytical database technologies.
Experience working with Snowflake, BigQuery, ClickHouse, Azure Synapse, or similar analytical database technologies.
Programming & Query Languages: Advanced SQL skills, including query optimization, execution planning, and performance tuning.Strong Python skills for data pipeline development, automation, transformation, and integration with production systems.
Advanced SQL skills, including query optimization, execution planning, and performance tuning.
Strong Python skills for data pipeline development, automation, transformation, and integration with production systems.
Data Pipeline & Orchestration ToolsExperience building and managing data pipelines using dbt, Airflow, Prefect, or similar orchestration and transformation tools.
Experience building and managing data pipelines using dbt, Airflow, Prefect, or similar orchestration and transformation tools.
Architecture & SecurityStrong understanding of lakehouse architecture, data partitioning strategies, metadata management, and data security best practices.
Strong understanding of lakehouse architecture, data partitioning strategies, metadata management, and data security best practices.
Professional SkillsAbility to collaborate effectively across engineering, product, data science, and business teams.Strong communication skills with the ability to translate business requirements into scalable data solutions.Strong analytical and problem-solving skills with a focus on building scalable, maintainable systems.Ability to balance long-term platform strategy with near-term business priorities.
Ability to collaborate effectively across engineering, product, data science, and business teams.
Strong communication skills with the ability to translate business requirements into scalable data solutions.
Strong analytical and problem-solving skills with a focus on building scalable, maintainable systems.
Ability to balance long-term platform strategy with near-term business priorities.
Advanced SQL skills, including query optimization, execution planning, and performance tuning.
Strong Python skills for data pipeline development, automation, transformation, and integration with production systems.
Data Pipeline & Orchestration ToolsExperience building and managing data pipelines using dbt, Airflow, Prefect, or similar orchestration and transformation tools.
Experience building and managing data pipelines using dbt, Airflow, Prefect, or similar orchestration and transformation tools.
Architecture & SecurityStrong understanding of lakehouse architecture, data partitioning strategies, metadata management, and data security best practices.
Strong understanding of lakehouse architecture, data partitioning strategies, metadata management, and data security best practices.
Deep expertise with Databricks, Delta Lake, and Apache Spark for large-scale data processing, streaming ingestion, and data transformation.
Experience working with Snowflake, BigQuery, ClickHouse, Azure Synapse, or similar analytical database technologies.
Advanced SQL skills, including query optimization, execution planning, and performance tuning.
Strong Python skills for data pipeline development, automation, transformation, and integration with production systems.
Experience building and managing data pipelines using dbt, Airflow, Prefect, or similar orchestration and transformation tools.
Strong understanding of lakehouse architecture, data partitioning strategies, metadata management, and data security best practices.
Ability to collaborate effectively across engineering, product, data science, and business teams.
Strong communication skills with the ability to translate business requirements into scalable data solutions.
Strong analytical and problem-solving skills with a focus on building scalable, maintainable systems.
Ability to balance long-term platform strategy with near-term business priorities.