Data Architect/ Enablement Lead (AWS, Databricks)

Role: Data Enablement & Strategy Lead

Remote and travel

We are seeking a highly capable Data Enablement & Strategy Lead who can combine strategic leadership with handson technical delivery. This role will champion data platform adoption, accelerate enterprise data initiatives, and guide teams in building scalable solutions on Databricks and AWS. The ideal candidate brings deep technical expertise, strong execution ownership, and the ability to influence and align crossfunctional stakeholders. 

Key Responsibilities:

Leadership & Enablement

• Lead and guide data engineering teams to deliver scalable, reliable data solutions
• Establish and promote best practices, standards, and frameworks for data engineering and analytics
• Enable teams by removing technical blockers and improving delivery efficiency
• Drive alignment between business stakeholders, engineering teams, and architecture groups

Hands-on Technical Delivery

• Design, build, and optimize data pipelines using Databricks, PySpark, and SQL
• Implement end-to-end data solutions on AWS using services like S3, Glue, Lambda, Kinesis, and Redshift
• Contribute directly to development of batch, real-time, and streaming data pipelines
• Ensure implementation of scalable, secure, and cost-optimized data lakehouse architecture using Delta Lake
• Perform code reviews, performance tuning, and troubleshooting of complex data pipelines

Data Platform & Enablement

• Drive adoption of Databricks and AWS data platform capabilities across teams
• Establish standards for data ingestion, transformation, data quality, lineage, and metadata management
• Support governance, security, and compliance practices including RBAC, encryption, and masking
• Enable self-service analytics and data accessibility for BI and data science teams

Collaboration & Execution

• Work closely with BI teams, product owners, and enterprise architects
• Translate business requirements into scalable technical solutions
• Support AI/ML initiatives by enabling high-quality curated datasets
• Drive execution of roadmap items in alignment with leadership priorities

Required Skills & Qualifications:

• Strong hands-on experience with Databricks and Apache Spark
• Proficiency in Python, PySpark, and SQL
• Strong experience in AWS cloud services (S3, Glue, Lambda, Kinesis, Redshift)
• Experience designing and building end-to-end data pipelines
• Strong understanding of data lakehouse architecture (Delta Lake preferred)
• Proven experience in technical leadership or tech lead role
• Strong stakeholder management and communication skills
• Experience with CI/CD, Git, and DevOps practices
•  Partner with governance teams to enforce compliance and stewardship
• Implement costefficient design patterns
• Define orchestration standards for reliability and maintainability
• Act as a platform evangelist across the organization
• Influence enterprise data strategy and platform roadmap
• Prioritize initiatives based on business value and technical feasibility.

Nice to Have:

• Experience supporting or enabling AI/ML use cases and data science teams
• Familiarity with MLflow or Databricks ML ecosystem
• Experience with streaming platforms like Kafka or Kinesis
• Background in data governance, data quality frameworks, or metadata tools
• Experience working closely with executive leadership.