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Job Description

About the role:

As a Senior Technology Manager, you will lead large scale solution architecture design and optimization to provide streamlined insights to partners throughout the business. We are seeking an experienced and strategic individual who can lead end-to-end governance and delivery of large-scale AI and Data programs within the Health and Life Sciences domain. This role ensures effective program-level planning, estimation, execution, quality, and risk management, driving outcomes aligned with business objectives. The individual will play a key role in building and scaling technology consulting competencies, driving thought leadership, and engaging with senior stakeholders.

Responsibilities also include providing support on all aspects of Business Development work, PoV development, RFPs and proposals, shaping delivery approaches, and ensuring strong governance, predictable execution, and high-quality outcomes across complex programs and initiatives.

How you will contribute:

• Own end-to-end governance of data engineering programs, ensuring alignment to enterprise data strategy, architecture principles, and data governance standards.
• Act as the main governance point of contact for senior stakeholders, aligning business goals with data initiatives and providing clear visibility into program status and risks.
• Govern team capacity, capability, ensuring the right skill mix, productivity, and continuity across programs.
• Possess knowledge and experience of design, development, optimization, and maintenance of data architecture and pipelines adhering to ETL principles and business goals.
• Oversee development and maintenance of scalable data pipelines, driving new integrations using AWS native technologies and data bricks to support increases in data source, volume, and complexity.
• Lead the definition of data requirements and guide the ingestion, analysis, and validation of large-scale structured and unstructured data using big data tools and platforms.
• Lead the ad hoc data analysis, support standardization, customization and drive development of robust mechanisms to ingest, analyze, validate, normalize, and clean data.
• Possess knowledge and experience of writing unit/integration/performance test scripts and performing data analysis required to troubleshoot data related issues.
• Oversee processes and systems to drive data reconciliation and monitor data quality, ensuring production data is always accurate and available for key stakeholders, downstream systems, and business processes.
• Lead the evaluation, implementation and deployment of emerging tools and processes for analytic data engineering to improve productivity.
• Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes.
• Oversee and support the team with the solution to complex data problems to deliver insights that help achieve business objectives.
• Drive partnership with Business Analysts and Enterprise Architects to develop technical architectures for strategic enterprise projects and initiatives.
• Drive collaboration with Data Scientists, visualization developers and other data consumers to understand data requirements, and design solutions that enable advanced analytics, machine learning, and predictive modelling.
• Drive collaboration with AI/ML engineers to create data products for analytics and data scientist team members to improve productivity.
• Advise, consult, mentor and coach other data and analytic professionals on data standards and practices, promoting the values of learning and growth.
• Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.

Minimum Requirements/Qualifications:

• Bachelor’s degree in Engineering, Computer Science, Data Science, or related field
• 18+ years of experience in software development, data engineering, ETL, and analytics reporting development
• Health and Life sciences domain experience
• Expert in building and maintaining data and system integrations using dimensional data modelling and optimized ETL pipelines.
• Advanced experience utilizing modern data architecture and frameworks like data mesh, data fabric, data product design
• Experience with designing data integration frameworks capable of supporting multiple data sources, consisting of both structured and unstructured data
• Proven track record of designing and implementing complex data solutions
• Demonstrated understanding and experience using:
• Data Engineering Programming Languages (i.e., Python)
• Distributed Data Technologies (e.g., Pyspark)
• Cloud platform deployment and tools (e.g., Kubernetes)
• Relational SQL databases
• DevOps and continuous integration
• AWS cloud services and technologies (i.e., Lambda, S3, DMS, Step Functions, Event Bridge, Cloud Watch, RDS)
• Knowledge of data lakes, data warehouses, AI pipelines or similar
• Databricks/ETL
• IICS/DMS
• GitHub
• Event Bridge, Tidal
• Deep understanding of database architecture and administration
• Processes high proficiency in code programming languages (e.g., SQL, Python, Pyspark, AWS services) to design, maintain, and optimize data architecture/pipelines that fit business goals.
• Extracts, transforms, and loads data from multiple external/internal sources using Databricks Lakehouse/Data Lake concepts into a single, consistent source to serve business users and data visualization needs.
• Utilizes the principles of continuous integration and delivery to automate the deployment of code changes to elevate environments.
• Excellent written and verbal communication skills, including storytelling and interacting effectively with multifunctional teams and other strategic partners.
• Strong organizational skills with the ability to manage multiple projects simultaneously, operating as leading member across globally distributed teams.
• Strong problem solving and troubleshooting skills.
• Ability to work in a fast-paced environment and adapt to changing business priorities.

Preferred requirements:

• Master’s Degree in Engineering, Computer Science, Data Science, or related field
• Experience in a global working environment

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