Key Responsibilities

• Data Infrastructure Management: Design, develop, and maintain the data infrastructure, including databases, data pipelines, and ETL processes, to support efficient data storage, retrieval, and processing.
• Schema Design: Collaborate with data scientists, analysts, and other stakeholders to design database schemas that optimize data retrieval and storage while adhering to industry best practices.
• Data Modeling: Create and maintain data models and data dictionaries to ensure consistency and standardization across data sources and systems.
• Performance Optimization: Monitor and fine-tune database performance by identifying and resolving bottlenecks, optimizing queries, and implementing indexing strategies.
• ETL Development: Develop and maintain scalable Extract, Transform, Load (ETL) processes to ensure data quality, integrity, and timeliness.
• Data Security: Implement and maintain data security measures, including access controls, data encryption, and compliance with relevant regulations (e.g., GDPR, HIPAA).
• Data Quality and Governance: Establish data quality standards, perform data profiling, and implement data governance processes to ensure data accuracy, consistency, and completeness.
• Collaboration and Communication: Collaborate with cross-functional teams, including data scientists, analysts, software engineers, and business stakeholders, to understand data requirements and translate them into technical solutions. Communicate effectively to present complex technical concepts to non-technical stakeholders.
• Documentation: Document data infrastructure, processes, and technical specifications to ensure knowledge transfer and enable smooth maintenance and troubleshooting.
• Continuous Learning: Stay up-to-date with emerging technologies, trends, and best practices in data engineering and apply them to improve existing systems and processes.

Required Skills and Qualifications

• Bachelor's degree in Computer Science, Engineering, or a related field.
• 3-5 years of professional experience as a Data Engineer or in a similar role.
• Strong proficiency in working with relational databases, particularly PostgreSQL and SQL Server, including database design, querying, optimization, and performance tuning.
• Solid understanding of SQL and experience with advanced SQL concepts, such as subqueries, window functions, and stored procedures.
• Experience with data modeling and schema design, including normalization, denormalization, and indexing strategies.
• Strong knowledge of ETL processes and tools for data integration, transformation, and loading.
• Familiarity with data warehouse concepts and technologies (e.g., star schema, data lakes).
• Understanding of data security principles and experience implementing data security measures.
• Excellent problem-solving and analytical skills with the ability to work on complex data-related challenges.
• Strong communication and collaboration skills with the ability to work effectively in a cross-functional team environment.
• Attention to detail and a commitment to delivering high-quality work.
• Self-motivated and able to work independently with minimal supervision.
• Familiarity with other database systems, such as MySQL, Oracle, or MongoDB, is a plus.
• Knowledge of cloud platforms and services, such as AWS, Azure, or GCP, is a plus.

Equal Employment

• Medici is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.

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