Senior Data Scientist - Remote Position

About the Role

We are urgently seeking a Senior Data Scientist remote to join our innovative team at Hirenza. In this pivotal role, you will be responsible for designing, building, and maintaining the data infrastructure that underpins our analytics, machine learning models, and operational reporting. This position requires a hands-on professional who excels at working at the intersection of data engineering, modeling, and production systems. Your expertise will directly impact our ability to optimize processes, reduce costs, and deliver insights that drive strategic growth.

What You'll Do

• Design and evolve our lakehouse architecture on platforms such as Delta Lake on AWS or Azure, including storage layout, compute strategy, and performance SLAs.
• Build and maintain robust batch and streaming data pipelines utilizing Apache Spark (PySpark/Scala), Databricks Workflows, Azure Data Factory, and event-driven systems like Kinesis, Event Hubs, or Kafka.
• Develop and sustain analytical, machine learning-ready data models, semantic layers, and dimensional schemas tailored for BI and production environments.
• Implement observability and reliability features, including custom Spark metrics, anomaly detection, logging, and automated data quality checks to ensure system robustness.
• Optimize compute and storage performance through cluster tuning, caching, partitioning, and format selection, resulting in cost efficiencies.
• Enforce data governance policies, including role-based access control, row-level security, cataloging, lineage tracking, and compliance with regulations such as GDPR, HIPAA, FHIR, CCPA, and CDPA.
• Collaborate effectively with analytics, product, and platform teams to define service level agreements (SLAs), manage incident response, and establish data contract best practices.
• Mentor junior engineers, lead design reviews, and set standards for scalable and maintainable data systems that align with organizational goals.

Requirements

• Over 8 years of experience in data science or data engineering.
• Proficiency in Python and SQL is essential, with working knowledge of Scala or Java for Spark-based projects.
• 3-5 years of hands-on experience with Apache Spark and Databricks, including Delta Lake and performance tuning.
• Cloud experience with AWS services such as S3, EMR, Glue, Lambda, and Kinesis, or Azure equivalents.
• Experience with orchestration tools like Airflow or ADF, transformation frameworks such as dbt, and data warehouses like Snowflake, Redshift, or Databricks SQL.
• A solid foundation in data modeling, CI/CD workflows, Docker/Linux environments, and version control with Git.
• Ability to translate complex business needs into scalable data solutions and lead projects end-to-end.

Nice to Have

• Experience with advanced machine learning techniques.
• Familiarity with data visualization tools like Tableau or Power BI.
• Knowledge of big data technologies such as Hadoop or Kafka.

What We Offer

• A comprehensive benefits package designed to support your health, well-being, and professional growth.
• Competitive compensation commensurate with experience.
• Paid vacation, sick leave, holidays, and parental leave.
• Health insurance options including medical, dental, and vision plans.
• An Employee Assistance Program to support mental health and wellness.
• A 401(k) plan with a generous employer match.
• Life insurance coverage.
• Employee discounts on products and services, along with paid training opportunities.