🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, collaborating closely with Data Scientists and ML Engineers to enhance production workflows.
524 | Senior Data Support Engineer
📅 Aug 22, 2024
Data EngineeringSnowflakePythonSSIS
📜 Description
- Utilize Snowflake, Python, SSIS, SQL Server, DBT, and AWS in projects.
- Perform complex data manipulation, transformation, and analysis using SQL.
- Engage in data modeling, ELT development, and data warehousing techniques.
- Support QA and User Acceptance Testing processes.
🛠️ Requirements
- Must to have at least 5-6 years of experience with Data Engineering
- Must to have at least 5-6 years of experience with Snowflake, Python, SSIS, SQL Server, DBT, AWS.
- Proven track record as a Data Engineer with demonstrable experience in projects and solutions you’ve delivered
- Must to have at least 5 -6 years of experience with SQL for complex data manipulation, transformation, and analysis.
- Must to have at least 5 -6 years of experience with dbt core or dbt Cloud
- Must to have at least 5-6 years of experience with snowflake
- Must to have at least 5 -6years of experience with Python for scripting and custom data ingestion
- Must to have at least 5 -6 years of experience with data modelling, ELT development, and data warehousing techniques.
- Must to have at least 5 -6 years of experience with Git and GitHub Pull Request
- Must to have at least 5 -6 years of experience with supporting QA and User Acceptance Testing processes.
Full job description
Intetics Inc. is a leading American technology company providing custom software application development, distributed professional teams creation, software product quality assessment, and “all-things-digital” solutions, is looking for a Senior Data Support Engineer to enrich its team with a skilled professional.
Requirements
- Must to have at least 5-6 years of experience with Data Engineering
- Must to have at least 5-6 years of experience with Snowflake, Python, SSIS, SQL Server, DBT, AWS.
- Proven track record as a Data Engineer with demonstrable experience in projects and solutions you’ve delivered
- Must to have at least 5 -6 years of experience with SQL for complex data manipulation, transformation, and analysis.
- Must to have at least 5 -6 years of experience with dbt core or dbt Cloud
- Must to have at least 5-6 years of experience with snowflake
- Must to have at least 5 -6years of experience with Python for scripting and custom data ingestion
- Must to have at least 5 -6 years of experience with data modelling, ELT development, and data warehousing techniques.
- Must to have at least 5 -6 years of experience with Git and GitHub Pull Request
- Must to have at least 5 -6 years of experience with supporting QA and User Acceptance Testing processes.
Would be a plus:
- Good to have experience with GitHub Action
- Good to have experience with Fivetran.
- Good to have experience with Terraform.
- Good to have experience with with AWS cloud services, particularly (e.g., AWS Lambda, S3 and ECS).
- Good to have experience with Power BI
- Good to have experience with Azure Data Factory and Logic Apps.
- Good to have experience with the entertainment or ticketing industry.
- Good to have experience of data protection laws such as GDPR, CCPA and SOX.
Similar jobs
Search more Data Engineer jobs🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, focusing on Python, AWS, and ETL processes to enhance data-driven solutions.
🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, collaborating with Data Scientists and ML Engineers to enhance production workflows.
🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, focusing on Python, AWS, and ETL processes to enhance data-driven decision-making.
🕒 yesterday
As a Senior Data Engineer, you will build and operate large-scale data and machine learning pipelines, collaborating with Data Scientists and ML Engineers to enhance production workflows.