Data Analyst Engineer

PurpleLab is focused on healthcare data solutions, and they are seeking a Data Analyst Engineer to build and maintain data pipelines. This role involves ensuring high-quality data for analysis and collaborating with cross-functional teams to support data governance and reporting strategies.

Responsibilities:

• Design, develop, and maintain robust ETL (Extract, Transform, Load) processes to ensure seamless ingestion and transformation of the data to be housed in the Data Warehouse
• Utilize Airflow (or similar workflow orchestration tool) to manage data pipelines, including custom operators, sensors, and hooks
• Implement robust data quality checks and validation processes using tools like Spark and SQL
• Analyze data for trends and patterns to proactively identify and resolve data quality issues
• Partner with cross-functional teams (data science, business intelligence, etc.) to ensure data accuracy, consistency, and security
• Support the design, development, testing, and implementation of cost-effective data assimilation and reporting strategies
• Champion data governance best practices and stay up-to-date on emerging data technologies and trends
• Develop and implement data integration and consolidation techniques to ensure high-quality data transfers
• Document and conduct ad-hoc analyses to support business needs, sales efforts, and proposed solutions
• Collaborate on projects as needed from senior leadership
• Perform other duties as assigned to support business needs and company objectives

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field required
• 3+ years of experience in data engineering, ETL development, or a related role
• Proficiency in SQL, Python, and Spark for data transformation and analysis
• Experience working in an Agile environment, specifically scrum
• Experience working with workflow orchestration tools such as Apache Airflow
• Strong knowledge of ETL processes, data pipelines, and cloud-based data solutions (AWS, GCP, or Azure)
• Familiarity with data modeling, database design, and data warehousing concepts
• Understanding of data quality frameworks, governance best practices, and data security principles
• Strong problem-solving skills with the ability to analyze complex data sets and identify trends
• Ability to collaborate with cross-functional teams, including data science, business intelligence, and leadership
• Excellent communication and documentation skills to support technical and non-technical stakeholders
• Master's degree in Computer Science, Data Engineering, Information Systems, or a related field
• Experience in healthcare or life sciences
• Experience with big data technologies (e.g., Hadoop, Snowflake, Databricks)