We are seeking an experienced Data Consultant to design, develop, and optimize enterprise -grade data platforms across modern cloud ecosystems. The ideal candidate will have strong expertise in platforms such as Databricks, Snowflake, and Amazon Redshift, along with hands -on experience in scalable data engineering, cloud -native architectures, and performance optimization.

The candidate will play a key role in solution implementation, stakeholder communication, architecture design, mentoring junior engineers, and driving best practices across data platforms.

Key Responsibilities

- Design scalable, secure, and high -performance data architectures using Databricks, Snowflake, and Redshift.

- Develop and optimize ETL/ELT pipelines for batch and real -time processing.

- Build and tune Spark workloads and SQL -based transformations for large -scale data processing.

- Lead migration and modernization initiatives from traditional data warehouses to cloud -native data platforms.

- Implement Delta Lake best practices including partitioning, Z -ordering, optimization, and data lifecycle management.

- Design robust data models including Star Schema, Snowflake Schema, and Data Vault methodologies.

- Ensure governance, security, and access controls using frameworks such as Unity Catalog, RBAC, and cloud -native security services.

- Collaborate with business stakeholders, architects,



and engineering teams to translate business requirements into scalable technical solutions.

- Implement CI/CD pipelines and DevOps best practices for data engineering deployments.

- Work with orchestration and workflow management tools such as Airflow, ADF, or similar platforms.

- Mentor Associate Consultants and Engineers through technical guidance, code reviews, and best practices.

- Monitor and optimize platform performance, reliability, and cost efficiency.


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