Description

Design and build data lakehouse platforms that enable AI model development, analytics, and reporting.

Responsibilities

• Architect scalable data lakehouse and platform solutions based on client business and technical requirements.
• Define implementation roadmaps for data analytics, AI, and machine learning goals.
• Design data ingestion, storage, transformation, and governance solutions using Delta Lake, Apache Iceberg, or Apache Hudi.
• Develop ETL/ELT pipelines for structured and unstructured data.
• Lead cloud-based data platform strategies across AWS, Azure, or GCP.

Required Skills

• 12+ years of experience in data architecture, data engineering, or data platform roles.
• Expertise in modern data lakehouse architecture using Apache Spark, Delta Lake, Snowflake, or BigQuery.
• Hands-on experience with cloud platforms including AWS (S3), Azure (Data Lake), or GCP (BigQuery).
• Proficiency in distributed computing and data processing frameworks such as Hadoop, Spark, or Presto.
• Strong understanding of ETL/ELT pipeline design and orchestration frameworks like Airflow or dbt.
• Solid foundation in data modeling principles.
• Knowledge of data governance, security best practices, and compliance regulations like GDPR or HIPAA.
• Proven consulting experience assessing requirements and developing technical strategies.

Preferred Skills

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

Key Skills

Education

Any Graduate