Lead Data Engineer (Remote)

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Written by AI from the job title and company, not by Stryker, so some details may not match this job. The employer's own page has the real description.

Job Overview

The Lead Data Engineer at Stryker will play a pivotal role in driving data strategy and implementation within our organization. The candidate will lead a team of data engineers to design, develop, and manage scalable data pipelines and systems, ensuring data integrity and availability for analytical purposes. This position requires collaboration across various departments to leverage data insights and foster data-driven decision-making while adhering to industry best practices and compliance requirements.

Job Responsibilities

• Lead the development and optimization of data pipelines and ETL processes to enhance data quality and availability.
• Design and implement data models that support analytics, reporting, and machine learning initiatives.
• Collaborate with cross-functional teams to gather requirements and deliver data solutions that meet business needs.
• Ensure adherence to data governance policies and practices, including security, privacy, and compliance standards.
• Mentor and guide junior data engineers in best practices, coding standards, and data engineering concepts.
• Evaluate and select appropriate technologies and tools for data engineering tasks and team operations.
• Monitor and troubleshoot data systems and pipelines to ensure optimal performance and reliability.

Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field; a Master's degree is preferred.
• Minimum of 5 years of experience in data engineering or related fields, with a focus on data pipeline design and implementation.
• Proficient in programming languages such as Python, Java, or Scala.
• Strong experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB). Critical understanding of data warehousing concepts.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and data processing frameworks (e.g., Apache Spark, Apache Kafka).
• Demonstrated leadership skills with experience in team management and project oversight.
• Excellent problem-solving and analytical skills, with a keen attention to detail.

Technologies & Tools

The Lead Data Engineer will primarily work with cloud-based data solutions, leveraging tools and technologies such as AWS Redshift, Azure Data Lake, Apache Hadoop, Spark, and Docker for containerization. Familiarity with version control systems like Git and CI/CD practices is essential for streamlined collaboration and deployment. The role requires proficiency in analytical tools that support data visualization and reporting, such as Tableau or Power BI.

Ideal Candidates

Ideal candidates for this role will possess a strong foundation in data engineering principles, combined with excellent communication skills necessary for cross-department collaboration. They should demonstrate a proactive and innovative approach to problem-solving, continuously seeking opportunities to enhance data processes and contribute to strategic objectives. A commitment to maintaining high standards of quality and security in data handling, along with passion for mentoring and leading teams, will further distinguish successful candidates in this position.