Data Lakehouse/ Platform Architect

• Seeking an experienced Data Lakehouse/Platform Architect to design, architect, andbuild scalable data lakehouses or data platforms
• Work closely with clients to enable data science and analytics teams for AI modeldevelopment, reporting, and business intelligence
• Requires deep technical expertise in data architecture, cloud platforms, and big datatechnologies, along with a strong consulting background

Primary Skills:

• Proven experience (7+ years) in data architecture, data engineering, or data platformroles
• Expertise in modern data lakehouse architecture (Delta Lake, Apache Iceberg, ApacheHudi, Snowflake, BigQuery)
• Hands-on experience with cloud platforms (AWS, Azure, GCP) and their data services(AWS S3, Azure Data Lake, GCP BigQuery)
• Strong understanding of ETL/ELT pipeline design and orchestration frameworks (Airflow,dbt)
• Proficiency in distributed computing and data processing frameworks (Hadoop, Spark,Presto)
• Knowledge of data governance, security best practices, and compliance regulations(GDPR, HIPAA)
• Strong consulting skills to assess client requirements, develop technical strategies, andprovide recommendations

Secondary Skills:

• Familiarity with AI/ML model development lifecycle and data science workflows
• Experience with streaming data platforms (Kafka, Kinesis)
• Cloud platform certifications (AWS, Azure, GCP)

Roles & Responsibilities:

• Consult with clients to understand business and technical needs, designing scalableData Lakehouse/Data Platform solutions
• Define and implement data lakehouse roadmaps aligned with client goals in analytics,AI, and machine learning
• Architect data ingestion, storage, transformation, and governance solutions usingmodern data lakehouse technologies
• Lead cloud-based data platform strategies across AWS, Azure, or GCP, ensuring datamanagement best practices
• Develop ETL/ELT pipelines for structured and unstructured data, optimizing accessibilityfor Data Science and BI teams
• Ensure data security, governance, and compliance throughout the data lifecycle
• Collaborate with client teams, internal stakeholders, and partners to execute end-to-enddata platform projects
• Conduct technology assessments, evaluate emerging tools, and recommend best-fitsolutions
• Provide mentoring, training, and thought leadership on Data Lakehouse architecture,data modeling, and data pipeline best practices