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Develop, deploy and maintain data processing pipelines using cloud technology such as AWS, Kubernetes, Lambda, Kafka, Airflow, Redshift, S3, Glue, and EMR. 10+ years of experience in data engineering on distributed frameworks such as Spark, Databricks, Kafka Streams, Hadoop etc.
$226,000 - $361,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Net, C#, Qlik, Power BI, Machine Learning, Azure Data Factory, RedShift, UiPath, Cloud, RPA, AWS, Redshift, Kinesis, QuickSight, SageMaker, S3, Databricks, AWS Lake Formation, Snowflake, Python, Qlik, Athena, Data Pipeline, Glue, Star Schema, Data Modeling, Performance Tuning, SQL Individual salaries that are offered to a candidate are determined after consideration of numerous factors including but not limited to the candidate’s qualifications, experience, skills, and geography.
$100,000 - $155,000Full-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Hand-on knowledge of ETL and data warehouse technologies (i.e. dbt, Databricks, BigQuery, Redshift, Airflow, Snowflake) As part of our data team, you'll work with stakeholders across the business, including finance, marketing, engineering, product, operations, and support.
Full-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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We use tools like DBT, Airflow, Redshift, ElasticSearch, Atlan, and Retool to orchestrate data pipelines and define workflows. Experience working both real-time systems like Kinesis, Kafka, Flink, and batch data pipelines in Redshift, Presto, and Data Lakes.
$187,200 - $280,800 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Experience managing cloud data warehouses (Snowflake, BigQuery, Redshift, etc.) Experience implementing real-time and batch data pipelines with tight SLOs and complex transformation requirementsProficiency in data architecture and modeling concepts, such as Kimball or Data VaultExpertise in data engineering tooling, such as ingesting, testing, transformations, lineage, orchestration, and/or semantic layers.
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Familiarity with data warehousing concepts, tools and monitoring highly recommended (Airbyte, DBT, Bigquery, Redshift) Scale architectural design work through data engineering, data governance, and solutions architecture.
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Comfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto, Athena, Spark, DBT. The ideal candidate will be adept in navigating the data stack and able to support initiatives in all facets from analytics/data engineering and product analytics to machine learning.
ExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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About The Role & TeamWe are seeking a Sr. Data Engineer to join our Data Engineering team within our Enterprise Data Insights organization to build data solutions, design and implement ETL/ELT processes and manage our data platform to enable our cross functional stakeholders.
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Experience with big data and workflow management technologies like Hadoop, Spark, Redshift, Athena, Airflow, etc. The Data Platform team is responsible for ingestion of tens of thousands of events per second, data Lakehousing (Databricks), OLTP stores (Hbase, OpenSearch) and APIs. The customers of the Data Platform are the internal business units who use it for data engineering, AI/ML, and Business Intelligence.
$145,000 - $190,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Knowledge of data engineering and data warehousing concepts, including RedShift, Redshift Spectrum, AWS Glue, AWS Lambda. Experience with data visualization tools such as Tableau, MixPanel, Google Looker.
Full-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Exposure to big data platforms – Snowflake, Redshift, Azure, Matillion, Alteryx, etc. Partner with cross functional teams such as data science, data engineering, product analysts, experimentation and instrumentation teams to contribute to advanced models (MMM, MTA), data pipelines and instrumentation, and build testing roadmap.
Full-timeExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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Collaborate with product, data engineering and broader engineering teams to refine data additions to the data warehouse, lead scoring, and dynamic lead routing incentive systems.
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Strong experience identifying complex business insights directly via SQL (Databricks, Redshift, etc.) Familiarity with customer data augmentation, segmentation, custom audiences, and consumer marketing datasets.
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Proficient in Data Warehouse technologies (e.g. Snowflake, AWS Redshift, etc) and in AWS data pipelines (Lambda, AWS glue, Step functions, Airflow etc) Design, build, and maintain robust and scalable data pipelines using Python, AWS services (e.g., S3, Redshift, Glue, Fivetran.
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Have 7-10 years of experience working with data warehouse/data lake and ETL architectures, cloud data warehouses (Redshift, Snowflake, RDS) , and experience in Python and SQL, preferably at companies with fast-growing and evolving data needs.
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redshift data engineering jobs in San Francisco, CA
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