Engineering Team Lead - Data

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Requirements:

• 7+ years of experience in data engineering, 2+ years of experience in a lead role.
• Solid understanding of data lake, lakehouse, and warehouse data architectures.
• Deep hands-on expertise in AWS cloud architecture and data-related services, patterns, and practices, inclusive of S3, EMR, Glue, Athena, Redshift, QuickSight, Kinesis or equivalent streaming, SQS and other queue/messaging components, Lambda, Step Functions, Airflow or other job management as appropriate.
• Strong command of SQL, Python and related Python libraries.
• Knowledge of data visualization tools (QuickSight preferred) and advanced analytics techniques.
• Proven track record of successfully building and scaling reliable, secure, cost efficient, and performant data and analytics solutions.
• Demonstrable experience with designing and implementing data quality processes.
• Excellent leadership and communication skills, with the ability to motivate and inspire teams.
• Strong analytical and problem-solving skills, with a focus on data-driven decision-making.
• Ability to work collaboratively across diverse teams and prioritize effectively in a fast-paced environment.
• An understanding of data security and data privacy and related regulatory requirements.
• Prior experience working in a global environment with offshore team members.
• Prior experience in education technology product development and learning analytics is strongly preferred.
• Recent, relevant experience with Machine Learning and Generative AI as they apply to data analytics uses cases for discovery, analysis, and predictive use cases is strongly preferred.
• Bachelor’s degree in computer science or related engineering/technical discipline

Responsibilities:

• Provide technical and people leadership and direction for the data team, setting goals, defining technical approaches, architecture, planning and executing work following Agile practices to consistently deliver on commitments.
• Partner closely with product management, application, SRE, and security teams to build consensus on needed capabilities, designs, APIs, infrastructure, and ensure security and privacy of data.
• Oversee the architecture and implementation of data pipelines, structured and unstructured storage, data transformation, data warehouses, analytics solution, and data APIs.
• Ensure the delivery of high-quality, timely, and accurate data solutions.
• Drive the adoption of best practices in data quality, and security.
• Monitor emerging technologies and trends in data and analytics to recommend and implement innovative solutions.
• Manage project timelines, budgets, and resources to meet internal and customer commitments.
• Build and maintain strong relationships with internal stakeholders, external vendors, and customers.
• Recruit, develop, and retain strong talent for the data team, inclusive of employees and off-shore/near-shore partners.