Data Engineer

About Our Client

Our client is an international professional services brand of firms, operating as partnerships under the brand. It is the second-largest professional services network in the world

Job Description

Qualifications

⎯ Bachelor's degree in Computer Engineering, Computer Science or related discipline, Master's Degree preferred.

⎯ 3+ years of ETL design, development, and performance tuning using ETL tools such as SSIS/ADF in a multi-dimensional Data Warehousing environment.

⎯ 3+ years of experience with setting up and operating data pipelines using Python or SQL

⎯ 3+ years of advanced SQL Programming: PL/SQL, T-SQL

⎯ 3+ years of experience working with Snowflake, including Snowflake SQL, data modeling, and performance optimization.

⎯ Strong hands-on experience with cloud data platforms such as Azure Synapse and Snowflake for building data pipelines and analytics workloads. ⎯ 3+ years of strong and extensive hands-on experience in Azure, preferably data heavy / analytics applications leveraging relational and NoSQL databases, Data Warehouse and Big Data

⎯ 3+ years of experience with Azure Data Factory, Azure Synapse Analytics, Azure Analysis Services, Azure Databricks, Blob Storage, Databricks/Spark, Azure SQL DW/Synapse, and Azure functions.

⎯ 3+ years of experience in defining and enabling data quality standards for auditing, and monitoring.

⎯ Strong analytical abilities and a strong intellectual curiosity.

⎯ In-depth knowledge of relational database design, data warehousing and dimensional data modeling concepts

⎯ Understanding of REST and good API design.

⎯ Strong collaboration, teamwork skills, excellent written and verbal communications skills.

⎯ Self-starter and motivated with ability to work in a fast-paced development environment.

⎯ Agile experience highly desirable.

⎯ Proficiency in the development environment, including IDE, database server, GIT, Continuous Integration, unit-testing tool, and defect management tools.Preferred Skills:

* Strong Knowledge of Data Engineering concepts (Data pipelines creation, Data Warehousing, Data Marts/Cubes, Data Reconciliation and Audit, Data Management).

* Strong working knowledge of Snowflake, including warehouse management, Snowflake SQL, and data sharing techniques.

* Experience building pipelines that source from or deliver data into Snowflake in combination with tools like ADF and Databricks.

* Working Knowledge of Dev-Ops processes (CI/CD), Git/Jenkins version control tool, Master Data Management (MDM) and Data Quality tools.

* Strong Experience in ETL/ELT development, QA and operation/support process (RCA of production issues, Code/Data Fix Strategy, Monitoring and maintenance).

* Hands on experience in Databases like (Azure SQL DB, MySQL/, Cosmos DB etc.), File system (Blob Storage), Python/Unix shell Scripting.

* ADF, Databricks and Azure certification is a plus.

The Successful Applicant

Qualifications

⎯ Bachelor's degree in Computer Engineering, Computer Science or related discipline, Master's Degree preferred.

⎯ 3+ years of ETL design, development, and performance tuning using ETL tools such as SSIS/ADF in a multi-dimensional Data Warehousing environment.

⎯ 3+ years of experience with setting up and operating data pipelines using Python or SQL

⎯ 3+ years of advanced SQL Programming: PL/SQL, T-SQL

⎯ 3+ years of experience working with Snowflake, including Snowflake SQL, data modeling, and performance optimization.

⎯ Strong hands-on experience with cloud data platforms such as Azure Synapse and Snowflake for building data pipelines and analytics workloads. ⎯ 3+ years of strong and extensive hands-on experience in Azure, preferably data heavy / analytics applications leveraging relational and NoSQL databases, Data Warehouse and Big Data

⎯ 3+ years of experience with Azure Data Factory, Azure Synapse Analytics, Azure Analysis Services, Azure Databricks, Blob Storage, Databricks/Spark, Azure SQL DW/Synapse, and Azure functions.

⎯ 3+ years of experience in defining and enabling data quality standards for auditing, and monitoring.

⎯ Strong analytical abilities and a strong intellectual curiosity.

⎯ In-depth knowledge of relational database design, data warehousing and dimensional data modeling concepts

⎯ Understanding of REST and good API design.

⎯ Strong collaboration, teamwork skills, excellent written and verbal communications skills.

⎯ Self-starter and motivated with ability to work in a fast-paced development environment.

⎯ Agile experience highly desirable.

⎯ Proficiency in the development environment, including IDE, database server, GIT, Continuous Integration, unit-testing tool, and defect management tools.Preferred Skills:

* Strong Knowledge of Data Engineering concepts (Data pipelines creation, Data Warehousing, Data Marts/Cubes, Data Reconciliation and Audit, Data Management).

* Strong working knowledge of Snowflake, including warehouse management, Snowflake SQL, and data sharing techniques.

* Experience building pipelines that source from or deliver data into Snowflake in combination with tools like ADF and Databricks.

* Working Knowledge of Dev-Ops processes (CI/CD), Git/Jenkins version control tool, Master Data Management (MDM) and Data Quality tools.

* Strong Experience in ETL/ELT development, QA and operation/support process (RCA of production issues, Code/Data Fix Strategy, Monitoring and maintenance).

* Hands on experience in Databases like (Azure SQL DB, MySQL/, Cosmos DB etc.), File system (Blob Storage), Python/Unix shell Scripting.

* ADF, Databricks and Azure certification is a plus.