Data Solution Architect ( Data Engineering)

What you will do

Role Description:

We are seeking a Data Solutions Architect to design, implement, and optimize scalable and high-performance data solutions that support enterprise analytics, AI-driven insights, and digital transformation initiatives. This role will focus on data strategy, architecture, governance, security, and operational efficiency, ensuring seamless data integration across modern cloud platforms. The ideal candidate will work closely with engineering teams, business stakeholders, and leadership to establish a future-ready data ecosystem, balancing performance, cost-efficiency, security, and usability. This position requires expertise in modern cloud-based data architectures, data engineering best practices, and Scaled Agile methodologies.

Roles & Responsibilities:

• Design and implement scalable, modular, and future-proof data architectures that support enterprise data lakes, data warehouses, and real-time analytics.
• Develop enterprise-wide data frameworks that enable governed, secure, and accessible data across various business domains.
• Define data modeling strategies to support structured and unstructured data, ensuring efficiency, consistency, and usability across analytical platforms.
• Lead the development of high-performance data pipelines for batch and real-time data processing, integrating APIs, streaming sources, transactional systems, and external data platforms.
• Optimize query performance, indexing, caching, and storage strategies to enhance scalability, cost efficiency, and analytical capabilities.
• Establish data interoperability frameworks that enable seamless integration across multiple data sources and platforms.
• Drive data governance strategies, ensuring security, compliance, access controls, and lineage tracking are embedded into enterprise data solutions.
• Implement DataOps best practices, including CI/CD for data pipelines, automated monitoring, and proactive issue resolution, to improve operational efficiency.
• Lead Scaled Agile (SAFe) practices, facilitating Program Increment (PI) Planning, Sprint Planning, and Agile ceremonies, ensuring iterative delivery of enterprise data capabilities.
• Collaborate with business stakeholders, product teams, and technology leaders to align data architecture strategies with organizational goals.
• Act as a trusted advisor on emerging data technologies and trends, ensuring that the enterprise adopts cutting-edge data solutions that provide competitive advantage and long-term scalability.

What we expect of you

Must-Have Skills:

• Experience in data architecture, enterprise data management, and cloud-based analytics solutions.
• Expertise in Databricks, cloud-native data platforms, and distributed computing frameworks.
• Strong proficiency in modern data modeling techniques, including dimensional modeling, NoSQL, and data virtualization.
• Experience designing high-performance ETL/ELT pipelines and real-time data processing solutions.
• Deep understanding of data governance, security, metadata management, and access control frameworks.
• Hands-on experience with CI/CD for data solutions, DataOps automation, and infrastructure as code (IaaC).
• Proven ability to collaborate with cross-functional teams, including business executives, data engineers, and analytics teams, to drive successful data initiatives.
• Strong problem-solving, strategic thinking, and technical leadership skills.
• Experienced with SQL/NOSQL database, vector database for large language models
• Experienced with data modeling and performance tuning for both OLAP and OLTP databases
• Experienced with Apache Spark
• Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops

Good-to-Have Skills:

• Good to have deep expertise in Biotech & Pharma industries
• Experience with Data Mesh architectures and federated data governance models.
• Certification in cloud data platforms or enterprise architecture frameworks.
• Knowledge of AI/ML pipeline integration within enterprise data architectures.
• Familiarity with BI & analytics platforms for enabling self-service analytics and enterprise reporting.

Education and Professional Certifications

• Doctorate Degree with 6-8 + years of experience in Computer Science, IT or related field

OR

• Masters degree with 8-10 + years of experience in Computer Science, IT or related field

OR

• Bachelors degree with 10-12 + years of experience in Computer Science, IT or related field
• AWS Certified Data Engineer preferred
• Databricks Certificate preferred

Soft Skills:

• Excellent analytical and troubleshooting skills.
• Strong verbal and written communication skills
• Ability to work effectively with global, virtual teams
• High degree of initiative and self-motivation.
• Ability to manage multiple priorities successfully.
• Team-oriented, with a focus on achieving team goals.
• Ability to learn quickly, be organized and detail oriented.
• Strong presentation and public speaking skills.