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As a Data Engineer at Huron, you must have knowledge of building and operating data pipelines. You will be building data pipeline solutions by designing, adopting, and applying big data strategies and architectures. You must have knowledge of (or the ability to learn quickly) scalable system implementations with a focus on complex data processing and analytics pipelines. You must demonstrate an understanding of data integration, data transformation, data modeling, and data cleansing. The Data Engineer must be able to demonstrate innovative approaches to complex problems which deliver industry-leading experiences for business stakeholders. We are looking for those with a strong computer science foundation and the ability to quickly get up to speed with technologies they may not be familiar with. The ability to learn and grow quickly is a must.
RESPONSIBILITIES
QUALIFICATIONS
TECHNOLOGIES WE USE
Cloud (AWS) / Data Warehouse (Redshift / Athena) / SQL/ dbt / Python / Data extraction and Integration Tools (AWS DMS, Glue/Lambda/ECS) /AWS SDK / Cube.js / Visualization Tools (AWS QuickSight) / DevOps Tools (Azure DevOps/AWS CDK/CloudFormation)
EDUCATION EXPERIENCE
Education
UG: B.Tech/B.E. in Production/Industrial
PG: MCA in Computers
Job ID: 109132155
Skills:
snowflake , Apis, Apache Spark, Sql, Databricks, Azure, Python, AWS, CI CD, IaC, data modeling principles, SageMaker, data integration tools, DevOps concepts, message streaming platforms, Amazon Bedrock
Skills:
SQL Server, Sql, Dashboarding, Data Transformation, Star Schema, Snowflake schema, Dimensional Modelling, Qlik Sense Architecture design, Qlik Sense best practices, Qlik Sense development, Qlik Management Console, set analysis, data-modelling, reporting techniques
Skills:
Agile, JIRA, Python, Sql, AWS, Data Pipelines, data administration
Skills:
snowflake , Java, S3, BigQuery, Scala, Apache Spark, Redshift, Sql, Gcp, Docker, Databricks, Apache Beam, Azure, Kubernetes, Python, AWS, HDFS
Skills:
Data Modeling, Apache Spark, Sql, DataFrame APIs
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