Data Quality Engineer

3 days ago

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Loopback Analytics

WebsiteLinkedInAll Job Openings

Population Analytics • Evidence-Based Models • Post-Acute Care Coordination • Medication Adherence • Community-Based Services

51 - 200 employees

Founded 2009

⚕️ Healthcare Insurance

💊 Pharmaceuticals

🧬 Biotechnology

💰 Private Equity Round on 2023-06

Description

• Enforce and maintain robust data quality standards and protocols. • Monitor and evaluate data quality metrics to identify and address anomalies and inconsistencies. • Participate in efforts to identify and address data-related errors and discrepancies promptly. • Collaborate with technical and non-technical teams to resolve issues and prevent future occurrences. • Develop and implement data quality assurance processes and procedures. • Design and execute data quality checks and validations to ensure accuracy, completeness, and consistency of data. • Collaborate with data engineers and data analysts to understand data pipelines and identify potential sources of data quality issues. • Investigate and report data quality issues in a timely manner. • Develop and maintain data quality metrics and reports to monitor and communicate the health of our data assets. • Develop, document and maintain manual and automation tests for ETL data pipelines using various frameworks like PyTest or Great Expectations. • Work closely with cross-functional teams to define data quality requirements and standards. • Provide technical expertise and guidance on data quality best practices. • Automate data quality monitoring and validation processes using Python and Databricks. • Perform data profiling and analysis to identify patterns and trends in data quality issues. • Stay up-to-date with industry trends and emerging technologies related to data quality management.

Requirements

• A deep understanding of data management principles, data governance, data integration, data quality, and data architecture. • 3-5 years experience with proficiency in working with relational databases, NoSQL databases, data warehouses, and big data technologies such as Snowflake, Databricks, Spark, etc. • Bachelor's or Master's degree or relevant experience in a field such as Computer Science, Data Science, Healthcare Informatics. • Experience in working with healthcare data and familiarity with the intricacies of healthcare data management. • Proven experience working as a Data Quality Engineer or in a similar role. • Strong proficiency in Python for data manipulation, analysis, and automation. • Hands-on experience with Databricks for data processing and analytics. • Familiarity with Snowflake data warehouse platform is a plus. • Solid understanding of data quality concepts, frameworks, methodologies, commercial tools and best practices. • Experience with data profiling tools and techniques. • Travel expectation less than 15%