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About the role
Required Qualifications - 5 to 8 years of experience in data engineering roles, with 3+ years of hands-on experience working with Snowflake and dbt in production environments, and demonstrable project experience with Matillion (Data Productivity Cloud or Matillion ETL ) Technical Skill s: Cloud Data Warehouse & Transformation Stac k:1. Expert-level knowledge of SQL and Snowflake, including performance optimization, storage layers, query profiling, clustering, and cost managemen t.2. Experience in dbt development: modular model design, macros, tests, documentation, and version control using Gi t.3. Hands-on experience with Matillion Data Productivity Cloud, including Designer pipelines, orchestration jobs, transformation jobs, variables, shared jobs, and Git-based project managemen t. Orchestration and Integrati on:1. Proficiency in orchestrating workflows using dbt Cloud, Matillion Data Productivity Cloud, Airflow, or Azure Data Facto ry.2. Comfortable working with data ingestion from cloud storage (e.G., Azure Data Lake, AWS S3) and APIs, including building Matillion pipelines that consume REST APIs and leverage native SaaS connecto rs. Data Modelling and Architect ure:1. Dimensional modelling (Star/Snowflake schemas), Slowly changing dimensi ons.2. Knowledge of contemporary data warehousing princip les.3. Experience implementing Medallion Architecture (Bronze/Silver/Gold layers) using a combination of Matillion for ingestion and staging and dbt for downstream transformati ons.4. Experience working with Parquet, JSON, CSV, or other data form ats. Programming Langu ages:1. Python: For data transformation, notebook development, automation, and extending Matillion via Python script compon ents.2. SQL: Strong grasp of SQL for querying and performance tu ning.3. Jinja (nice to have): Exposure to Jinja for advanced dbt develop ment. Data Engineering & Analytical S kills:1. ETL/ELT pipeline design and optimization across dbt and Mati llion.2. Exposure to AI/ML data pipelines, feature stores, or MLflow for model tracking (good to have).3. Exposure to data quality and validation frame works. Security & Gove rnance:1. Experience implementing data quality checks using dbt tests and Matillion validation comp onents.2. Data encryption, secure key management, and security best practices for Snowflake, dbt, and Matillion (credential management, OAuth, workspace/environment isol ation). - Soft Skills & Lea - dership:Ability to thrive in client-facing roles with competing/changing priorities and fast-paced delivery - cycles.Stakeholder Communication: Collaborate with business stakeholders to understand objectives and convert them into actionable data engineering - designs.Project Ownership: End-to-end delivery including design, implementation, and mon - itoring.Mentorship: Guide junior engineers and establish best practices; Build new skill in t - he team.Agile Practices: Work in sprints, participate in scrum ceremonies, story est imation. - E ducation: Bachelors or masters degree in computer science, Data Engineering, or a relat ed field. Certifications such as Snowflake SnowPro Advanced, dbt Certified Developer, and Matillion Associate or Professional Certification (Data Productivity Cloud) ar e a plus. Required Qualifications - 5 to 8 years of experience in data engineering roles, with 3+ years of hands-on experience working with Snowflake and dbt in production environments, and demonstrable project experience with Matillion (Data Productivity Cloud or Matillion ETL ) Technical Skill s: Cloud Data Warehouse & Transformation Stac k:1. Expert-level knowledge of SQL and Snowflake, including performance optimization, storage layers, query profiling, clustering, and cost managemen t.2. Experience in dbt development: modular model design, macros, tests, documentation, and version control using Gi t.3. Hands-on experience with Matillion Data Productivity Cloud, including Designer pipelines, orchestration jobs, transformation jobs, variables, shared jobs, and Git-based project managemen t. Orchestration and Integrati on:1. Proficiency in orchestrating workflows using dbt Cloud, Matillion Data Productivity Cloud, Airflow, or Azure Data Facto ry.2. Comfortable working with data ingestion from cloud storage (e.G., Azure Data Lake, AWS S3) and APIs, including building Matillion pipelines that consume REST APIs and leverage native SaaS connecto rs. Data Modelling and Architect ure:1. Dimensional modelling (Star/Snowflake schemas), Slowly changing dimensi ons.2. Knowledge of contemporary data warehousing princip les.3. Experience implementing Medallion Architecture (Bronze/Silver/Gold layers) using a combination of Matillion for ingestion and staging and dbt for downstream transformati ons.4. Experience working with Parquet, JSON, CSV, or other data form ats. Programming Langu ages:1. Python: For data transformation, notebook development