STIIIZY
Architect, build, and run the data backbone that powers analytics, machine learning, and operational reporting. Responsible for designing, evolving, and maintaining our Data Lake/Lakehouse infrastructure to meet business needs and ensure reliability, scalability, and security.
Key Responsibilities:
Design and evolve our Data Lake/Lakehouse (Delta Lake) on AWS and/or Azure, including storage layout, security, compute strategy, and SLAs.
Develop and maintain batch and streaming ETL/ELT pipelines using Apache Spark (PySpark/Scala), Databricks Workflows, and/or Azure Data Factory.
Integrate data sources via APIs, CDC, and message buses (Kinesis/Event Hubs/Kafka).
Build and maintain dimensional/semantic models for Databricks SQL to support BI and production ML features.
Implement observability, logging, anomaly detection, and data quality testing.
Manage CI/CD processes, infrastructure as code, and automated testing.
Optimize data processing performance and costs.
Enforce governance policies, including RBAC, row-level security, cataloging, lineage, and PII compliance.
Collaborate with cross-functional teams to define SLAs, manage incident response, and establish best practices.
Mentor team members and lead design/code reviews.
Perform other duties as needed in support of business objectives assigned by supervisor.
What Success Looks Like in 6-12 Months
Critical domains are flowing through trustworthy, observable pipelines with
30–50% reduction in time-to-insight on key analytics use cases via dbt and semantic layers. Meaningful cost savings from tuned compute/storage without sacrificing latency. Stakeholders trust the platform, alerts are actionable, incidents are rare and boring. Technical Skills & Abilities: Expert-level Python and SQL skills; working knowledge of Scala/Java for Spark. Advanced experience with Apache Spark and Databricks. Strong AWS and/or Azure cloud infrastructure skills. Proficiency in orchestration tools (Airflow, ADF) and transformation tools (dbt). Experience with Snowflake, Redshift, or Databricks SQL. Knowledge of data modeling, testing, CI/CD, Docker/Linux, and Git. Ability to translate business needs into scalable data products. Education & Experience: Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent work experience). 8+ years of data engineering experience. 3–5+ years working with Apache Spark and Databricks. Experience delivering end-to-end data solutions in production environments. Nice to Have Experience building custom Spark listeners/metrics, event-driven architectures, or low-latency streaming. FHIR/healthcare data pipelines and DLT troubleshooting. Power BI/Tableau/Looker dashboarding to close the loop on quality and impact. Exposure to governance frameworks (catalog/lineage, RLS, data contracts) and MLOps (feature stores, model monitoring). Requirements: Must be at least 21 years of age. Must be able to push, pull, move, and/or lift a minimum of 15 lbs. to a minimum height of 5 feet and able to push, pull, move, and/or carry such weight a minimum distance of 50 feet. Prolonged periods of standing, sitting at a desk, and working on a computer. Must be able to access and navigate each department at the organization's facilities. Ability to get in and out of the vehicle and walk up and down stairs during your shift. Must be able to stand, sit for prolonged periods of time, bend, kneel, squat, and twist. Ability to travel occasionally for team meetings or conferences. We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Benefits & Compensation: Health, Dental, and Vision Insurance. Employee Assistance Program. 401k with generous employer match. Life Insurance. Employee discounts on products and services.
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30–50% reduction in time-to-insight on key analytics use cases via dbt and semantic layers. Meaningful cost savings from tuned compute/storage without sacrificing latency. Stakeholders trust the platform, alerts are actionable, incidents are rare and boring. Technical Skills & Abilities: Expert-level Python and SQL skills; working knowledge of Scala/Java for Spark. Advanced experience with Apache Spark and Databricks. Strong AWS and/or Azure cloud infrastructure skills. Proficiency in orchestration tools (Airflow, ADF) and transformation tools (dbt). Experience with Snowflake, Redshift, or Databricks SQL. Knowledge of data modeling, testing, CI/CD, Docker/Linux, and Git. Ability to translate business needs into scalable data products. Education & Experience: Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent work experience). 8+ years of data engineering experience. 3–5+ years working with Apache Spark and Databricks. Experience delivering end-to-end data solutions in production environments. Nice to Have Experience building custom Spark listeners/metrics, event-driven architectures, or low-latency streaming. FHIR/healthcare data pipelines and DLT troubleshooting. Power BI/Tableau/Looker dashboarding to close the loop on quality and impact. Exposure to governance frameworks (catalog/lineage, RLS, data contracts) and MLOps (feature stores, model monitoring). Requirements: Must be at least 21 years of age. Must be able to push, pull, move, and/or lift a minimum of 15 lbs. to a minimum height of 5 feet and able to push, pull, move, and/or carry such weight a minimum distance of 50 feet. Prolonged periods of standing, sitting at a desk, and working on a computer. Must be able to access and navigate each department at the organization's facilities. Ability to get in and out of the vehicle and walk up and down stairs during your shift. Must be able to stand, sit for prolonged periods of time, bend, kneel, squat, and twist. Ability to travel occasionally for team meetings or conferences. We provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Benefits & Compensation: Health, Dental, and Vision Insurance. Employee Assistance Program. 401k with generous employer match. Life Insurance. Employee discounts on products and services.
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