Lead Data Product Engineer (Senior data engineer)

Bootminds; United States; Hybrid; USD 140,000 - 190,000; Full time

Job summary

Bootminds is seeking a Lead Data Product Engineer to lead the design, development, and delivery of enterprise-scale data products supporting commercial analytics and BI initiatives within Life Sciences. This senior role combines technical leadership, architecture oversight, stakeholder engagement, and hands-on data engineering to ensure scalable, business-aligned data solutions.

Responsibilities include overseeing end-to-end data product delivery, building pipelines on Databricks, Snowflake, AWS

Qualifications

• Senior-level data engineering experience in enterprise analytics.
• Experience with data lakehouse concepts and medallion architecture.
• Strong Python and SQL skills.

Responsibilities

• Lead end-to-end data product delivery and architecture.
• Design scalable data pipelines and ELT/ETL workflows.
• Collaborate with stakeholders and provide governance and documentation.
• Mentor engineers and drive DevOps practices.

Skills

Data Engineering

Cloud Platforms

SQL

Python

Airflow

Databricks

Snowflake

Power BI

Leadership

Stakeholder Management

Tools

Bitbucket

Git

CI/CD

DevOps

Job description

Lead Data Product Engineer (Senior Data Engineer)

We are seeking an experienced Lead Data Product Engineer to lead the design, development, and delivery of enterprise-scale data products supporting commercial analytics and business intelligence initiatives within the Life Sciences and Pharmaceutical domain. This role combines technical leadership, architecture oversight, stakeholder engagement, and hands-on data engineering responsibilities to ensure delivery of robust, scalable, and business-aligned data solutions.

Key Responsibilities

• Technical Leadership & Architecture: Lead end-to-end engineering delivery for data products while ensuring alignment with enterprise technical standards and best practices. Review solution architectures, design patterns, data models, and integration approaches. Drive technical design discussions and provide guidance on scalability, performance, security, and maintainability. Govern and optimize existing Medallion Architecture implementations to support evolving business requirements. Ensure adherence to data engineering and cloud engineering standards across project deliverables.
• Hands-on Data Engineering: Design, develop, and optimize scalable data pipelines and ELT/ETL workflows. Build and maintain data solutions using Databricks, Snowflake, AWS, and Airflow. Perform code reviews and contribute directly to development activities as required. Implement robust data quality, monitoring, and operational support processes. Troubleshoot performance bottlenecks and drive continuous platform improvements.
• Stakeholder Management: Collaborate with business stakeholders, product owners, analytics teams, and technical leadership. Translate business requirements into scalable technical solutions. Provide regular updates on delivery progress, risks, dependencies, and technical recommendations. Partner with cross-functional teams to ensure data products meet business objectives and user expectations.
• Governance & Delivery Oversight: Establish and maintain engineering documentation, technical specifications, and operational runbooks. Provide governance oversight across development, testing, deployment, and transition activities. Support knowledge transfer and ensure successful onboarding of support and maintenance teams. Drive adoption of engineering best practices, code quality standards, and DevOps processes.

Requirements

• Technical Skills: Data Engineering & Cloud Platforms, AWS Cloud Services, Databricks, Snowflake, Apache Airflow, SQL (Advanced), Python, Bitbucket, CI/CD pipelines, Git-based development practices, Data Lakehouse Concepts, Medallion Architecture, Data Modeling, Data Governance Frameworks, Performance Optimization, Power BI (Primary Visualization Platform), KPI and Dashboard Development, Commercial Analytics Reporting.
• Domain Experience: Strong experience in Life Sciences / Pharmaceutical Commercial Analytics. Understanding of pharma data assets, sales analytics, patient analytics, commercial operations, and reporting ecosystems. Experience supporting commercial data platforms and analytics solutions for pharmaceutical organizations.
• Leadership Requirements: Proven experience leading engineering delivery across multiple workstreams. Ability to mentor engineers and drive engineering excellence. Strong communication and stakeholder management skills. Experience managing technical reviews, solution governance, and delivery quality.
• Preferred Qualifications: Experience working in Agile delivery environments. Exposure to large-scale cloud data modernization initiatives. Experience integrating analytics and reporting solutions with enterprise data platforms. Knowledge of data product management principles and modern data engineering practices.

Work Arrangements

• Location: Flexible / Hybrid
• Experience: ~10 Years