Lead Data Engineer [Digital Engineering & Transformation]

Our technology powers the world’s top companies to bring innovation to life and manage their IP portfolio. As a leader in our industry, we are embarking on a transformative journey to leverage big data, data lakes, and lakehouse technologies to streamline our data services and support our product lines with scalable, efficient, and high-quality data solutions.

We are looking for a Lead Data Engineer for our IP Maintenance products and services to spearhead the design and implementation of a simplified data service over a highly distributed data system.

This position will report to the Director of IP Technology and with a focus on digital transformation strategy, this role would work closely with product leaders, business operations, engineering teams, and other stakeholders to align on strategic goals and ensure delivery of innovative digital products and highly automated experiences using AI / ML technologies.

This role is critical in harnessing the power of Big Data, Lakehouse, Data Virtualization, Transformation and Integration technologies to enhance our product offerings and drive business growth.

The ideal candidate must be hands-on and will have a strong background in data engineering, with proven experience in developing and deploying large-scale data solutions in a cloud environment, must be metrics-focused and obsessed with Cloud native and DevOps technologies.

In this role, you will have the opportunity to make a lasting impact on the digital transformation journey, drive customer-centric innovation, and the ideal candidate will have a background of running transformation projects in similar disruptive industries such as Digital Payments or Fintech.

About You Experience, Education, Skills, and Accomplishments

• Bachelor’s in Computer Science or an equivalent experience in software development, with a minimum of 7 years experience in developing and delivering business transformation projects or products using data engineering and AI / ML technologies.
• Minimum of 5 years in leading engineering teams, with demonstrated experience in building high-performing, best in class engineering teams for a high-growth software product environment.
• Minimum of 5 years’ experience in data lake / lakehouse, distributed systems and data, data virtualization, microservices, and machine learning.
• Minimum of 5 years’ experience working with data structures, data streaming and pipelines, search, training and inference algorithms, event driven patterns and middleware technologies.
• Minimum of 5 years of hands-on skills in Python, Apache Spark, Hive, Cassandra, Snowflake, Elastic, Lucene, DataBricks, Hadoop, Redshift, Scala, Java, or other relevant technologies in data engineering.
• Minimum of 5 years’ experience building containerized applications and deploying them to public or private clouds, such as Amazon Web Services (AWS), Microsoft Azure, or similar providers, end-to-end SaaS applications, and highly scalable software products.
• Minimum of 5 years’ experience with automated delivery pipelines, agile delivery, and test-driven development and real-time data processing (e.

g., Kafka, Spark Streaming).

It would be great if you also had...

• Masters degree in Computer Science
• Experience in functional decomposition of legacy products and migrating to modern microservices architecture.
• Experience delivering products against plan in a fast-paced, multi-disciplined, distributed-responsibility and often ambiguous environment
• Experience in automated delivery pipelines, agile delivery, and test-driven development.
• Analytical and quantitative skills; experience using hard data and metrics to back up assumptions and develop business cases

What will you be doing in this role?

• Lead the design and development of a scalable and simplified data service using big data, data lakes, data virtualization, and / or data lakehouse technologies.
• Partnering closely with the Product, Technology and Business Operations teams to evolve and accelerate the execution of the product roadmap to maximize the current suite of digital solutions and innovate next generation solutions that will drive transformations.
• Leading and managing a set of engineering-driven initiatives from ideation through delivery to production of high impact digital transformation and platform modernization initiatives utilizing data engineering and AI / ML technologies, while optimizing Agile practices and methodologies to enhance speed, flexibility, and delivery efficiency
• Implement robust data ingestion, processing, and distribution pipelines to ensure timely and accurate data availability across the organization.
• Drive the adoption of best practices in data governance, quality, and lifecycle management, ensuring data integrity and compliance with regulatory standards.
• Establishing and executing a talent management strategy inclusive of hiring new talent and associated hiring practices, as well as upskilling existing talent to achieve the overall vision for data as a service.
• Act as a technical authority in software design, systems integration, and data services, guiding technical solutions and ensuring adherence to the highest security and privacy standards.
• Leading and mentoring a team, fostering a culture of collaboration, innovation, and excellence.
• Actively collaborating with the leadership team to propose technology investments for continued innovation and value creation in alignment with the overall vision and strategy.
• Remain current on emerging technologies and industry trends, proactively identifying opportunities for new product development.

About the Team

We are a cutting-edge Software Engineering team, part of the larger Technology organization focused on evolving our customer and user experience through innovation and transformation initiatives that leverages AI / ML to create new capabilities and products.

Our mission includes building digital products and services that alters the traditional approach to Intellectual Property processes and practices within the industry.

Hours of Work

• Full time, permanent
• Hybrid working schedule of 2-3 days / week on site
• Must live within a commutable distance to our Alexandria, VA or Philadelphia, PA office locations
• Flexible working hours to align with globally distributed teams and stakeholders.

Clarivate is an Equal Opportunity Employer Vets / Minorities / Women / Disabled