Technogen International Company
Data Engineer
Technogen International Company, Madison, Wisconsin, us, 53774
Please Note: As of July 22, 2021, our team will require that all candidate submissions include a LinkedIn profile. Please do not submit any candidates that do not have a LinkedIn.
Mid-Sr level (at least 2 year)ASAP 12/31/23 (potential to extend up to 3 yrs or convert)100% remote; potential to convert, but must live near hubStart date: asap in JanuaryThis team works on Change Data Capture (CDC) pipeline. Optimizing pipelines for efficiency, make pipeline changes (ex. Create a lambda) to make the pipeline better to reduce CPUsProjects:
V11 (legacy platform) and V4 (new platform)Core technology skillset: Python, AWS, SQL, Spark and ETL experience required.V11 uses AWS, Glue, Lambda, S3, SQL.V4 uses AWS, Spoon (repository), Pentaho. Exposure to Pentaho a plus (will train on this).Strong work experience in building data ingestion, ETL pipelines using AWS platform managed services such as AWS glue, AWS Data Pipeline, Amazon S3.Data engineering knowledge and prior experience with data lakes, data warehouses (e.g. star schema storage), understanding of different database architecturesData modeling, data mapping and SQL expertise by leveraging it being able to develop complex data transformation and storage solutionsExcellent data analysis, SQL query writing, ETL and incident managements skillsGCP experience a plus as they are eventually going to GoogleExcellent Communications as well as independent self-starter.Type of projects/data: policy data; claims data; quote data; user patternsBetween ETL ingestion/Data storage-excluding Tableau, ETL validation consume 70% of the time of the engineer and 30% would be building new solutions and work on side projects internallyLooking for someone to keep the lights on/Maintenance work on our legacy systemAWS experience required. GCP experience is a plus.Support on-call (adjust hours to stay within 40 hour work week). On call est. every 5-7 weeks.Familiarity with how BI tools ingest data
Required Skills : Mid-Sr level (at least 2 year) ASAP ? 12/31/23 (potential to extend up to 3 yrs or convert) 100% remote; potential to convert, but must live near hub Start date: asap in January -This team works on Change Data Capture (CDC) pipeline. Optimizing pipelines for efficiency, make pipeline changes (ex. Create a lambda) to make the pipeline better to reduce CPUs -Projects: V11 (legacy platform) and V4 (new platform) -Core technology skillset: Python, AWS, SQL, Spark and ETL experience required. -V11 uses AWS, Glue, Lambda, S3, SQL. -V4 uses AWS, Spoon (repository), Pentaho. Exposure to Pentaho a plus (will train on this). -Strong work experience in building data ingestion, ETL pipelines using AWS platform managed services such as AWS glue, AWS Data Pipeline, Amazon S3. -Data engineering knowledge and prior experience with data lakes, data warehouses (e.g. star schema storage), understanding of different database architectures -Data modeling, data mapping and SQL expertise ? by leveraging it being able to develop complex data transformation and storage solutions -Excellent data analysis, SQL query writing, ETL and incident managements skills -GCP experience a plus as they are eventually going to Google -Excellent Communications as well as independent self-starter. -Type of projects/data: policy data; claims data; quote data; user patterns -Between ETL ingestion/Data storage-excluding Tableau, ETL validation consume 70% of the time of the engineer and 30% would be building new solutions and work on side projects internally -Looking for someone to keep the lights on/Maintenance work on our legacy system -AWS experience required. GCP experience is a plus. -Support on-call (adjust hours to stay within 40 hour work week). On call est. every 5-7 weeks. -Familiarity with how BI tools ingest dataBasic Qualification :Additional Skills :Rank :B1Requested Date :2023-01-05
Mid-Sr level (at least 2 year)ASAP 12/31/23 (potential to extend up to 3 yrs or convert)100% remote; potential to convert, but must live near hubStart date: asap in JanuaryThis team works on Change Data Capture (CDC) pipeline. Optimizing pipelines for efficiency, make pipeline changes (ex. Create a lambda) to make the pipeline better to reduce CPUsProjects:
V11 (legacy platform) and V4 (new platform)Core technology skillset: Python, AWS, SQL, Spark and ETL experience required.V11 uses AWS, Glue, Lambda, S3, SQL.V4 uses AWS, Spoon (repository), Pentaho. Exposure to Pentaho a plus (will train on this).Strong work experience in building data ingestion, ETL pipelines using AWS platform managed services such as AWS glue, AWS Data Pipeline, Amazon S3.Data engineering knowledge and prior experience with data lakes, data warehouses (e.g. star schema storage), understanding of different database architecturesData modeling, data mapping and SQL expertise by leveraging it being able to develop complex data transformation and storage solutionsExcellent data analysis, SQL query writing, ETL and incident managements skillsGCP experience a plus as they are eventually going to GoogleExcellent Communications as well as independent self-starter.Type of projects/data: policy data; claims data; quote data; user patternsBetween ETL ingestion/Data storage-excluding Tableau, ETL validation consume 70% of the time of the engineer and 30% would be building new solutions and work on side projects internallyLooking for someone to keep the lights on/Maintenance work on our legacy systemAWS experience required. GCP experience is a plus.Support on-call (adjust hours to stay within 40 hour work week). On call est. every 5-7 weeks.Familiarity with how BI tools ingest data
Required Skills : Mid-Sr level (at least 2 year) ASAP ? 12/31/23 (potential to extend up to 3 yrs or convert) 100% remote; potential to convert, but must live near hub Start date: asap in January -This team works on Change Data Capture (CDC) pipeline. Optimizing pipelines for efficiency, make pipeline changes (ex. Create a lambda) to make the pipeline better to reduce CPUs -Projects: V11 (legacy platform) and V4 (new platform) -Core technology skillset: Python, AWS, SQL, Spark and ETL experience required. -V11 uses AWS, Glue, Lambda, S3, SQL. -V4 uses AWS, Spoon (repository), Pentaho. Exposure to Pentaho a plus (will train on this). -Strong work experience in building data ingestion, ETL pipelines using AWS platform managed services such as AWS glue, AWS Data Pipeline, Amazon S3. -Data engineering knowledge and prior experience with data lakes, data warehouses (e.g. star schema storage), understanding of different database architectures -Data modeling, data mapping and SQL expertise ? by leveraging it being able to develop complex data transformation and storage solutions -Excellent data analysis, SQL query writing, ETL and incident managements skills -GCP experience a plus as they are eventually going to Google -Excellent Communications as well as independent self-starter. -Type of projects/data: policy data; claims data; quote data; user patterns -Between ETL ingestion/Data storage-excluding Tableau, ETL validation consume 70% of the time of the engineer and 30% would be building new solutions and work on side projects internally -Looking for someone to keep the lights on/Maintenance work on our legacy system -AWS experience required. GCP experience is a plus. -Support on-call (adjust hours to stay within 40 hour work week). On call est. every 5-7 weeks. -Familiarity with how BI tools ingest dataBasic Qualification :Additional Skills :Rank :B1Requested Date :2023-01-05