Data Engineering Lead

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Seeking an experienced and highly skilled Data Engineering Technical Lead to spearhead the design, development, and optimization of robust and scalable data pipelines and data infrastructure. This role requires a deep understanding of data engineering principles, advanced proficiency in distributed data processing technologies, and a proven track record of leading technical teams in an agile environment. The Technical Lead will play a critical role in shaping our data architecture, ensuring data quality and governance, and enabling data-driven initiatives across the organization, particularly within the healthcare and supply chain logistics domains. This role is 100% remote.

 

The work:

• Lead, mentor, and guide a team of data engineers in best practices for data pipeline development, data modeling, and infrastructure management. Provide technical oversight and ensure adherence to architectural standards.
• Drive the design and implementation of highly scalable, reliable, and efficient data architectures, including data lakes, data warehouses, and streaming platforms. Define technical roadmaps and strategies for data engineering initiatives.
• Design, develop, and maintain complex ETL/ELT processes and data pipelines using modern data engineering tools and frameworks (e.g., Apache Spark, Kafka, Airflow). Ensure data ingestion, transformation, and loading processes are optimized for performance and reliability.
• Establish and enforce data governance policies, data quality standards, and data security protocols. Implement robust monitoring and alerting for data pipelines and data quality issues.
• Leverage expertise in cloud-based data platforms (e.g., AWS, Azure, GCP) to design and implement cloud-native data solutions, optimizing for cost, performance, and scalability.
• Collaborate closely with product owners, data scientists, data analysts, and other engineering teams to translate business requirements into technical specifications and deliver data solutions that align with strategic objectives. Act as a primary interface with customers, business stakeholders, and cross-functional teams to gather requirements, provide updates, and ensure alignment on data initiatives.
• Identify and resolve complex data-related performance bottlenecks and architectural challenges. Implement strategies for query optimization and data storage efficiency.
• Actively participate in agile ceremonies, including sprint planning, backlog refinement, daily stand-ups, and sprint reviews, contributing to a culture of continuous delivery and improvement. Lead and own the full Software Development Life Cycle (SDLC) for data solutions, from conceptualization and design through deployment, testing, and operational support.
• Create and maintain comprehensive technical documentation, including data flow diagrams, architectural designs, data dictionaries, and operational runbooks.

 

Here’s what you need:

• Experience with SQL, data modeling, and building ETL pipelines.
• Knowledge of data management fundamentals and data storage principles.
• Experience in coding and automating processes.
• Cloud Data Services experience through certification, education, or hands-on experience
• Demonstrated experience with CI/CD practices for data pipelines and infrastructure as code (IaC).

 

Bonus points if you have:

• Bachelor's degree in Computer Science, Data Engineering, or a related field.
• Experience in the healthcare or supply chain logistics industry, particularly with large-scale enterprise data.
• Familiarity with data visualization tools (e.g., Tableau, PowerBI) and their integration with data platforms.
• Experience with data orchestration tools (e.g., Apache Airflow, Prefect).
• Knowledge of machine learning operationalization (MLOps) and data science integration.
• Familiarity and experience with AI/ML (LLMs, Chatbot development) and the use of Databricks, Delta Lake, and Palantir Foundry.
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