Data Analyst

Data Analyst at Quantzig Data Analyst at Quantzig in Oak Park, California Posted in 2 days ago.

Type:

full-time

Job Description:

Role Summary This role supports commercial pharma sales analytics operations and enhancements, working across modern data platforms such as Databricks, Apache Airflow, Apache Spark, and Amazon S3. The focus is on maintaining and improving data pipelines, enabling scalable data processing, and supporting business-critical sales analytics use cases. Key Responsibilities Develop and optimize complex SQL logic using Spark SQL for large-scale datasets Manage and monitor data pipelines across Apache Airflow and Databricks, including job execution, failure triage, and ensuring timely data availability Execute data validation, reconciliation, and quality checks across source and processed layers (e.g., Amazon S3) to maintain accuracy and reliability Support recurring business reporting and analytics processes (KPIs, performance tracking, incentive compensation, QBR datasets) ensuring SLA adherence Identify and implement improvements in pipeline performance and scalability using Apache Spark / SQL and automation Build and maintain ETL/ELT pipelines using Python and Spark Enable sales analytics use cases including KPIs, QBRs, incentive compensation, call activity, and targeting Monitor, troubleshoot, and optimize pipelines, including serverless components like AWS Lambda Ensure data quality, validation, and reconciliation across upstream and downstream systems Collaborate with business and analytics teams to translate requirements into data solutions Maintain documentation for pipelines, datasets, and business logic Core Skills & Experience Strong SQL expertise (joins, aggregations, window functions, performance tuning) Hands-on experience with Databricks and Apache Spark / Spark SQL Experience with Apache Airflow Proficiency in Python for data processing Experience with AWS ecosystem (Amazon S3, AWS Lambda) Understanding of pharma commercial / sales analytics (KPIs, IC, QBRs, field performance) Strong analytical thinking and problem-solving Effective communication and stakeholder collaboration Additional Context (Good to Have) Experience with field force / territory-level analytics Exposure to production support models, SLA management, and pipeline monitoring Familiarity with data governance and access control in regulated environments

Mandatory:

SQL, Databricks, Apache Spark, AWS (Amazon S3, AWS Lambda), Pharma Commercial Analytics, Apache Airflow